| PHUSE US |
2026 |
Balancing Privacy and Utility with Smart Anonymisation [presentation] |
Zach Weingarden |
source |
13 |
| PHUSE APAC |
2026 |
Machine Learning Algorithms to Explore the Relationship Between Primary Obsessive-Compulsive Disorder (OCD) and Co-morbid Depression Symptoms |
Ajay Kumar Singh,
Sabyasachi Mukherjee |
source
presentation source |
12 |
| PHUSE EU |
2025 |
Diversity, Inclusion and Equality Its Just Good Science! |
Roxanne McGuire,
Chris Ward |
source
presentation source |
19 |
| MWSUG |
2025 |
Large-Scale Time Series Forecasting in Model Studio |
Danny R. Modlin |
source |
39 |
| SESUG |
2025 |
Large-Scale Time Series Forecasting in Model Studio |
Danny R. Modlin |
|
39 |
| SESUG |
2025 |
The Missing Piece |
Cali M. Davis |
|
17 |
| WUSS |
2025 |
Large-Scale Time Series Forecasting in Model Studio |
Danny R. Modlin |
source |
39 |
| MWSUG |
2024 |
Charting Your Organization's Machine Learning Roadmap |
Ryan Paul Lafler |
source |
7 |
| SESUG |
2024 |
Charting Your Organization's Machine Learning Roadmap |
Ryan Paul Lafler |
source |
7 |
| WUSS |
2024 |
Benefits, Challenges, and Opportunities with SAS and Open-Source Software (OSS) Integration [presentation] |
Kirk Paul Lafler,
Ryan Paul Lafler,
Joshua J. Cook,
Stephen B. Sloan,
Anna T. K. Wade |
source |
33 |
| WUSS |
2024 |
Charting Your Organization's Machine Learning Roadmap |
Ryan Paul Lafler |
source |
6 |
| PharmaSUG |
2024 |
Reconstruction of Individual Patient Data (IPD) from Published Kaplan-Meier Curves Using Guyot-s Algorithm: Step-by-Step Programming in R |
Ajay Gupta,
Natalie Dennis |
source |
10 |
| WUSS |
2023 |
A Beginner's Step-by-Step Guide to Digital Marketing Data Mining and Analysis Using SAS |
Mahsa Tahmasebi Ghorabi,
Leon Rod Davoody |
source |
7 |
| WUSS |
2023 |
Getting a Handle on All of Your SAS 9.4 Usage |
Stephen B. Sloan |
source |
6 |
| SESUG |
2023 |
Exploring the Skills Needed by the Data Scientist / Analytics Professional |
Kirk Paul Lafler |
source |
14 |
| SESUG |
2023 |
Getting a Handle on All of Your SAS 9.4 Usage |
Stephen B. Sloan |
source |
6 |
| PharmaSUG |
2023 |
Exploring the spread of COVID-19 in the United States using unsupervised graph-based machine learning |
Kostiantyn Drach,
Iryna Kotenko |
source |
39 |
| PHUSE US |
2023 |
Cluster analysis vs. graph-based machine learning: the battle of the strongest in pattern recognition |
Kostiantyn Drach,
Iryna Kotenko |
source
presentation source |
31 |
| PHUSE EU |
2022 |
Standards Subject to Change: Data Standards Flexibility in an Evolving Landscape [presentation] |
Gina Wood,
Alison Banda |
source |
28 |
| SESUG |
2022 |
Exploring the Skills Needed by the Data Scientist |
Kirk Paul Lafler |
source |
13 |
| SESUG |
2022 |
To Lend, or Not to Lend, That Is the Question! Evaluating Loan Application with Machine Learning |
Rafae Abdullah,
Sucharitha Vallabhaneni,
Jaideep Muley |
source |
17 |
| WUSS |
2022 |
Data mining for the online retail industry: Customer segmentation and assessment of customers using RFM and k-means |
Gowtham Varma Bhupathiraju |
source |
9 |
| WUSS |
2022 |
Exploring the Skills Needed by the Data Scientist |
Kirk Paul Lafler |
source |
13 |
| PharmaSUG |
2022 |
Getting a Handle on All of Your SAS 9.4 Usage |
Stephen B. Sloan |
source |
7 |
| PharmaSUG |
2022 |
Potential features analysis affect Covid-19 spread |
Yida Bao,
Philippe Gaillard |
source |
11 |
| SESUG |
2021 |
Use SAS Enterprise Miner Workstation 15.1 to Do Predictive Analysis for Mobile Strategy Games Industry |
Chun Du |
source |
11 |
| SGF |
2021 |
Detecting Online Recruitment Fraud |
Matthew Fruge,
Noah Heinrich |
source |
6 |
| SGF |
2021 |
Next-Generation Data Mining and Machine Learning: Python and SAS Together at Last |
George S. Habek,
Suman Kumar Das |
source
presentation |
24 |
| SGF |
2021 |
Pandemic Pandemonium |
Hannah Flynt,
Maryam Taherirani,
Sean Everett,
Trinh Phan |
source |
7 |
| SGF |
2021 |
SAS Time Series Analysis & Forecasting (TSAF) at the Canada Revenue Agency (CRA), with COVID impacts |
Jason A. Oliver |
source
presentation |
22 |
| PHUSE EU |
2020 |
Understanding the Spread of COVID-19 in the United States Using Topology and Machine Learning for Time Series |
Iryna Kotenko,
Kostiantyn Drach |
source
video
presentation source |
32 |
| SESUG |
2020 |
Application and comparison with several types of Ensemble Algorithms |
Yida Bao,
Philippe Gaillard |
source |
6 |
| SESUG |
2020 |
Getting a Handle on All of Your SAS 9.4 Usage |
Stephen B. Sloan |
source |
6 |
| SGF |
2020 |
Automation in SAS Visual Data Mining and Machine Learning |
Wendy Czika |
source |
26 |
| SGF |
2020 |
Enhancing Academic Teaching of Data Science with SAS Viya for Learners |
Stefan Dimitrov Stoyanov |
source |
30 |
| SGF |
2020 |
Explanatory Machine Learning Model Plots for Epidemiological and Real-World Evidence Studies |
David Olaleye |
source |
22 |
| SGF |
2020 |
Exploring Online Drug Reviews using Text Analytics, Sentiment Analysis, and Data Mining Models |
Thu Dinh,
Goutam Chakraborty |
source |
23 |
| SGF |
2020 |
From Silos to Ecosystem - Evolution of Analytical Platforms at Elisa Corporation |
Prasanna Pandian |
source |
7 |
| SGF |
2020 |
Hate Speech Classification of social media posts using Text Analysis and Machine Learning |
Venkateshwarlu Konduri |
source |
7 |
| SGF |
2020 |
Machine Learning Approach to Combat the Opioid Epidemic |
Navjot Kaur |
source |
15 |
| SGF |
2020 |
Open Source Python & R Lang on our SAS Shared Grid (SSG) |
Thomas Ball |
source |
5 |
| SGF |
2020 |
SAS Enterprise Miner vs. Scikit-Learn - How do they recommend me good songs? [presentation] |
Raphael Lima |
source |
10 |
| SGF |
2020 |
SAS Grid Manager and SAS Viya: A Strong Relationship |
Edoardo Riva |
source |
20 |
| SGF |
2020 |
SAS Grid Manager: Inside Look into Grid-Launched Servers |
Murali Srinivasan |
source |
22 |
| SGF |
2020 |
Scalable Cloud-Based Time Series Analysis and Forecasting Using Open Source Software |
Javier Delgado |
source |
21 |
| SGF |
2020 |
The Plight of the Honeybee |
Rachael Bishop |
source |
8 |
| SGF |
2020 |
Using Analytics to Predict Tax Recovery and Prioritize Audits and Investigations in Canada |
Jason A. Oliver |
source |
19 |
| PharmaSUG |
2020 |
Detecting Side Effects and Evaluating the Effectiveness of Drugs from Customers' Online Reviews using Text Analytics, Sentiment Analysis and Machine Learning Models |
Thu Dinh,
Goutam Chakraborty |
source |
22 |
| PharmaSUG |
2020 |
Special Plots methods with diabetes disease data |
Yida Bao,
Zheran Wang,
Jingping Guo,
Philippe Gaillard |
source |
10 |
| PHUSE US |
2020 |
A Comparison of Machine Learning Algorithms for Binary Classification of Free-text Fields Using SAS, R, and Python |
Michael S Rimler |
source
presentation source |
12 |
| PHUSE EU |
2019 |
Building Integrated Clinical Ecosystems |
Stijn Rogiers |
source
presentation source |
4 |
| PHUSE EU |
2019 |
Sub-population Detection Using Graph-based Machine Learning |
Sergey Glushakov,
Kostiantyn Drach |
source |
28 |
| SESUG |
2019 |
Analyzing Airbnb reviews using SAS Text Miner and Predicting the factors contributing for higher ratings |
Ashlesha Sampathi |
source |
15 |
| SESUG |
2019 |
Glass Box Neural Networks |
Ross Bettinger |
source |
14 |
| SESUG |
2019 |
Hybrid Rare Event Sampling Technique |
Ross Bettinger |
source |
15 |
| SESUG |
2019 |
Identify physical and mobile DMV Site Locations in North Carolina |
Puneet Kumar,
Rajeshwar Dutt,
Matthew R Rogers |
source |
12 |
| SESUG |
2019 |
Improving Employee Satisfaction Through Text Analytics |
Luis David Martinez |
source |
15 |
| SESUG |
2019 |
Macros for Neural Network Modeling |
Ross Bettinger |
source |
23 |
| SESUG |
2019 |
Summarizing some conventional methods to classify a binary target |
Yida Bao,
Philippe Gaillard |
source |
10 |
| SESUG |
2019 |
Validating a Probability of Default model using SASEnterprise Miner Scorecard |
George Rezek |
source |
27 |
| SESUG |
2019 |
Validating Classification and Recidivism in Corrections Through Outcome Analytics |
Alan R. Mann |
source |
34 |
| SCSUG |
2019 |
Can Life Style Change Prevent Diabetes? |
Mounica Mandapati |
source |
11 |
| SCSUG |
2019 |
Pattern Analysis and Predictive Policing Using Socio-Economic Factors |
Trishla Mishra |
source |
12 |
| SCSUG |
2019 |
Strategizing P2P Investments using Socio-Economic Factors |
Priyabrata Thatoi |
source |
12 |
| SCSUG |
2019 |
Uplift Modeling in Retail Marketing using SAS |
Aashish Arjan Bugalia,
Agastya Komarraju,
Miriam McGaugh |
source |
15 |
| MWSUG |
2019 |
Classifying Risk in Life Insurance using Predictive Analytics |
Sai Gopi Krishna Govindarajula |
|
6 |
| MWSUG |
2019 |
Detecting Side Effects and Evaluating Effectiveness of Drugs from Customers' Online Reviews using Text Analytics and Data Mining Models |
Thu Dinh |
|
23 |
| MWSUG |
2019 |
Do undergraduates need prerequisites for common courses? |
Lin Qi,
Archana Chinnaswamy,
Miriam McGaugh |
|
6 |
| MWSUG |
2019 |
Taxi Ride Prediction: Does the Yellow Cab Supply Meet Customer Demands? |
Sreejita Biswas,
Miriam McGaugh |
|
12 |
| MWSUG |
2019 |
The SAS EG Process Flow: A Customizable Data Mining Tool in the Search for Healthcare Fraud |
Andrea McLain |
|
6 |
| WUSS |
2019 |
Bayesian Nonparametric Clustering in SAS |
Hend Aljobaily |
source |
9 |
| WUSS |
2019 |
Multi-Way (more than two) Splits In Decision Trees |
Russell M. Lavery |
source |
8 |
| PharmaSUG |
2019 |
An Introduction to the Process of Improving a Neural Network |
YuTing Tian |
source |
22 |
| SGF |
2019 |
A Comparison of Algorithmic and Epidemiologic Approaches for Modeling Predictors of Type II Diabetes |
Audrey Whittle |
source |
8 |
| SGF |
2019 |
An Introduction to the Process of Improving a Neural Network |
YuTing Tian |
source |
22 |
| SGF |
2019 |
Are You a Lifelong Learner? Validate Your Skills and Stand Out with SAS Certifications! |
Andrew Howell |
source |
12 |
| SGF |
2019 |
Asking the Right Questions: A study in Multiclass Imbalanced Classification for H1-B Visas |
Matthew Bunker,
Owen Kelly |
source |
7 |
| SGF |
2019 |
Distribution Transformer Health Monitoring and Predictive Asst Maintenance |
Prasenjit Shil,
Tom Anderson |
source |
11 |
| SGF |
2019 |
Exploring the Intentions of Entering Entrepreneurship for SAS Global Forum 2019 |
Surabhi Arya,
Prashant Gour,
Dhruv Sharma,
Jeroen Vanheeringen |
source |
7 |
| SGF |
2019 |
Factors Influencing Academic Performance |
Onkar Mayekar,
Miriam McGaugh |
source |
9 |
| SGF |
2019 |
Identifying Partisanship in Media Articles |
Alexander Lobman,
Lohit Bhandari,
Ravi Josyula,
Nhan Nguyen |
source |
7 |
| SGF |
2019 |
Increasing Operational Efficiency by Using SAS in an Automated Process for Credit Scoring Models |
Roberta Pimenta Moreira,
Leonardo de Lima Aguirre,
Alfredo Luiz Venzel de Oliveira |
source |
7 |
| SGF |
2019 |
Integration of the SAS Platform in a Business Analytic Curriculum |
Michael Gibbs,
Ronald Freeze |
source |
4 |
| SGF |
2019 |
Machine Learning and Predictive Analytics in SAS Enterprise Miner and SAS/STAT Software |
David Richard Cutler |
source |
21 |
| SGF |
2019 |
Playing Favorites: Our Top 10 Model Studio Features in SAS Visual Data Mining and Machine Learning |
Wendy Czika,
Peter Gerakios |
source |
16 |
| SGF |
2019 |
Predicting the success of a startup company |
Vrushank Shah,
Miriam McGaugh |
source |
11 |
| SGF |
2019 |
SAS Enterprise Miner and SAS Visual Data Mining and Machine Learning Hand Shake |
Jagruti Kanjia,
Dominique Latour,
Holly Sweeney |
source |
35 |
| SGF |
2019 |
Scouting in Soccer with Applied Machine Learning |
Vishal Gaurav,
Goutam Chakraborty |
source |
19 |
| SGF |
2019 |
Sparking Your Data Innovation: SAS Integration with Apache Spark |
Kumar Thangamuthu |
source |
15 |
| SGF |
2019 |
To Buy or to Create? Determining the Best Option for Student Success Models |
Stephanie R. Thompson |
source |
6 |
| SGF |
2019 |
Unsupervised Learning for Anomaly Detection in Securities Data |
Laura Rudolphi,
Chris A. Robinson |
source |
7 |
| SGF |
2019 |
Using Simulation Games to Teach Analytics |
Jean-François Plante,
Pierre-Majorique Léger,
Jean-François Michon,
Forough Karimi-Alaghehband,
Marc Fredette,
Michael Bliemel |
source |
7 |
| PHUSE US |
2019 |
An Open Clinical Data Quality Framework |
Vineet Jain |
source
presentation source |
11 |
| SCSUG |
2018 |
Are you in danger of stroke? An insight into the leading causes. |
Anjali Bansal |
source |
17 |
| SCSUG |
2018 |
City of Austin Community Perception and Satisfaction Analysis |
Eric Hart |
source |
11 |
| SCSUG |
2018 |
Machine Learning in Litigation Prediction - Workers' Compensation Litigation Propensity Predictive Model |
Mei Najim |
source |
17 |
| SCSUG |
2018 |
Mining ECAD and WCAD Public Record Data - ETL Guide to ECAD and WCAD |
Michael McCarthy |
source |
9 |
| SCSUG |
2018 |
Predicting the Federal Reserve?s Next Federal Funds Rate Decisions |
Nhan Nguyen |
source |
13 |
| SCSUG |
2018 |
Text Analysis of Users? Review for Airbnb |
Prashant Gour |
source |
7 |
| SESUG |
2018 |
A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma |
Hurricane Irma |
source |
11 |
| SESUG |
2018 |
ANALYSIS OF FACTORS INFLUENCING DROPOUTS IN SOPHOMORE ENROLLMENT |
Apoorva Chandrasekaran |
source |
14 |
| SESUG |
2018 |
Developing In-House Student Success Models |
Stephanie R. Thompson |
source |
6 |
| SESUG |
2018 |
Predicting the Risk of Attrition for Undergraduate Students using SAS Enterprise Miner |
Sivateja Reddy Kandula |
source |
12 |
| SESUG |
2018 |
Sentiments' Analysis of Users' Review to Improve 5 Star Rating Method for a Recommendation System |
Surabhi Arya |
source |
6 |
| SESUG |
2018 |
Text Mining to Predict College Admission Trends |
Shashikant Chebrolu |
source |
11 |
| SESUG |
2018 |
Undergraduate Student Retention, Can we catch them before they fall? |
Lohit Bhandari |
source |
6 |
| SESUG |
2018 |
Understanding Crime Pattern in United States by Time Series Analysis using SAS Tools |
Soumya Ranjan Kar Choudhury |
source |
6 |
| MWSUG |
2018 |
An Introduction to the Process of Improving a Neural Network |
YuTing Tian |
|
22 |
| MWSUG |
2018 |
Analyzing Amazon's Customer Reviews using SAS Text Miner for Devising Successful Product Launch Strategies |
Manideep Mellachervu,
Anvesh Reddy Minukuri |
|
13 |
| MWSUG |
2018 |
Analyzing YouTube comments on gun violence using SAS Viya and SAS Text Miner |
Sridevi Loya |
|
9 |
| MWSUG |
2018 |
How to Score Big with SAS Solutions: Various Ways to Score New Data with Trained Models |
Scott Koval |
|
6 |
| WUSS |
2018 |
Analyzing international assessments: An ensemble and model comparison approach |
Chong Ho Yu,
Hyun Seo Lee,
Siyan Gan,
Emily Lara |
source |
13 |
| WUSS |
2018 |
Deep neural nets in SAS Enterprise Miner |
Russell M. Lavery |
source |
49 |
| PHUSE US |
2018 |
Achieving Highest Quality and Usability of SEND through Industry and Regulatory Collaboration |
William Houser,
Lou Ann Kramer |
source |
7 |
| PHUSE US |
2018 |
Data Science Applications and Scenarios |
Edwin Ponraj Thangarajan,
Giri Balasubramanian |
source
presentation source |
13 |
| PHUSE US |
2018 |
Drug-Induced Liver Injury (DILI) Classification Using FDA-Approved Drug Labeling and FAERS Data - FDA |
Qais Hatim |
source
presentation source |
31 |
| PHUSE US |
2018 |
Mine the Gap: How the Role of Data Scientist Fills a Need in the Pharmaceutical Industry |
Michael S Rimler,
Jorine Putter |
source
presentation source |
8 |
| PHUSE US |
2018 |
Modeling and Text Analysis to Empower FAERS Adverse Event Mitigation |
Qais Hatim,
Emily McRae |
source
presentation source |
24 |
| PHUSE US |
2018 |
Upcoming Technology with Transformative Potential for Life Sciences |
Sameer Thapar |
source
presentation source |
3 |
| PharmaSUG |
2018 |
Mining Mass Fragments using SAS and Python for Metabolite Identification of Antibody-Drug Conjugates |
Hao Sun,
Kristen Cardinal |
source |
5 |
| SGF |
2018 |
A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma |
Bogdan Gadidov,
Linh H. Le |
source |
11 |
| SGF |
2018 |
A Cautionary Tale of Using Machine Learning within Credit Risk in the Utilities Industry |
Spiros Potamitis,
Paul Malley |
source |
8 |
| SGF |
2018 |
A Study of Modeling Approaches for Predicting Dropout in a Business College |
Helmut Schneider,
Xuan Wang |
source |
8 |
| SGF |
2018 |
Analysis of Nokia Customer Tweets with SAS Enterprise Minerand SAS Sentiment Analysis Studio [presentation] |
Vaibhav Vanamala |
source |
13 |
| SGF |
2018 |
Analyzing Theft Occurrences in Chicago Using SAS Enterprise Miner and SAS Enterprise Guide [presentation] |
Kunal Parekh,
Shikha Prasad |
source |
4 |
| SGF |
2018 |
Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease Classification |
Jessica Rudd |
source |
10 |
| SGF |
2018 |
Association Rule Mining of Polypharmacy Patterns in Health Care Data Using SAS Enterprise Miner |
Dingwei Dai |
source |
17 |
| SGF |
2018 |
Bayesian Concepts: An Introduction |
John Amrhein,
Fei Wang |
source |
10 |
| SGF |
2018 |
Bayesian Networks for Causal Analysis |
John Amrhein,
Fei Wang |
source |
11 |
| SGF |
2018 |
Big Data Analytic Models: The Challenges of Philosophies as Covariates in Higher Education |
Sean W. Mulvenon |
source |
10 |
| SGF |
2018 |
Bitcoin Price Forecasting Using Web Search and Social Media Data |
Travis Miller |
source |
22 |
| SGF |
2018 |
Bridging the Skills Gap between Post-Secondary Education Outcomes and Employment Opportunities |
Hong-Yu Xavier Fu,
Allan Esser |
source |
7 |
| SGF |
2018 |
Business Customer Value Segmentation for Strategic Targeting in the Utilities Industry Using SAS |
Paul Malley,
Spiros Potamitis |
source |
9 |
| SGF |
2018 |
Claim Analytics: A Litigation Prediction Case Study |
Mei Najim |
source |
18 |
| SGF |
2018 |
Claim Risk Scoring Using Survival Analysis Framework and Machine Learning with Random Forest |
Yuriy Chechulin |
source |
15 |
| SGF |
2018 |
Classifying and Predicting Spam Messages Using Text Mining in SAS Enterprise Miner [presentation] |
Mounika Kondamudi |
source |
22 |
| SGF |
2018 |
Data Science and SAS : A Data Science Perspecitve [presentation] |
Richard W. La Valley |
source |
32 |
| SGF |
2018 |
Enhancing Subscription-Based Business by Predicting Churn Likelihood |
Smitha Etlapur |
source |
12 |
| SGF |
2018 |
Examining the Drivers of Hospital Re-admission of Type-2 Diabetic patients |
Shashank Reddy Gudipati |
source |
9 |
| SGF |
2018 |
Flight 3411 and Its Aftermath: A Burlesque Analysis via Tweets |
Vinoth Kumar Raja,
Padmashri Janarthanam |
source |
22 |
| SGF |
2018 |
From Academy to Industry: An Experimental Student Journey [presentation] |
Francesco Costigliola |
source |
28 |
| SGF |
2018 |
From Unstructured Text to the Data Warehouse: Customer Support at the University of North Texas |
Nick Evangelopoulos |
source |
10 |
| SGF |
2018 |
Getting More Insight into Your Forecast Errors with the GLMSELECT and QUANTSELECT Procedures |
Gerhard Svolba |
source |
26 |
| SGF |
2018 |
How to Prevent Turnover of the Best and Most-Experienced Employees with SAS Enterprise Miner [presentation] |
Liyuan Liu,
Lauren Staples |
source |
4 |
| SGF |
2018 |
Identifying Semantically Equivalent Questions Using Singular Value Decomposition |
Varsha Reddy Akkaloori |
source |
6 |
| SGF |
2018 |
Image Classification Using SAS Enterprise Miner 14.1 |
Akshay Arora |
source |
5 |
| SGF |
2018 |
Make SAS Enterprise Miner Play Nicely with SAS Viya |
Beth Ebersole |
source |
31 |
| SGF |
2018 |
Measuring Response to the Ultimate Driving Machine: Consumer Sentiments and Brand Advertising |
Amit K Ghosh,
Goutam Chakraborty,
Praveen Kumar Kotekal |
source |
8 |
| SGF |
2018 |
Monte Carlo K-Means Clustering [presentation] |
Donald Wedding |
source |
227 |
| SGF |
2018 |
Mylan's EpiPen Controversy: Leveraging Text Analytics During a PR Crisis |
Nikhila Kambalapalli |
source |
14 |
| SGF |
2018 |
New Frontiers in Pricing Analytics [presentation] |
Sharat Mathur |
source |
22 |
| SGF |
2018 |
Performing Machine Learning Techniques in a Contextual Marketing Scenario |
Francisco Capetillo,
Alvaro Velasquez |
source |
11 |
| SGF |
2018 |
Retail Product Bundling: A New Approach |
Bruno Nogueira |
source |
18 |
| SGF |
2018 |
Robust Tuning for Machine Learning |
Alex Glushkovsky |
source |
22 |
| SGF |
2018 |
Scalable Cloud-Based Time Series Analysis and Forecasting |
Thiago Quirino,
Michael J. Leonard,
Ed Blair |
source |
22 |
| SGF |
2018 |
Sentiment Analysis of Netflix and Competitor Tweets to Classify Customer Opinions |
Rucha Jadhavar,
Agastya Komarraju |
source |
15 |
| SGF |
2018 |
Sentiment Analysis on YouTube Movie Trailer Comments to Determine the Impact on Box-Office Earnings |
Rishanki Jain |
source |
9 |
| SGF |
2018 |
The Ensemble of Neural Network and Gradient Boosting for the Prediction of Customer Profitability |
Sunny Lam |
source |
15 |
| SGF |
2018 |
The Ultimate Data-Driven Guide to U.S. Canned Craft Beers Using SAS Enterprise Miner 14.2 [presentation] |
Linyi Tang |
source |
3 |
| SGF |
2018 |
Time Series Feature Extraction |
Michele A. Trovero,
Michael J. Leonard |
source |
18 |
| SGF |
2018 |
To Show or Not to Show? Using SAS Solutions to Maximize Patient Scheduling In Medical Clinics |
Mia Lyst,
Yijie Li |
source |
8 |
| SGF |
2018 |
Top 10 Tips for SAS Enterprise Miner Based on 20 Years' Experience |
Melodie Rush |
source |
21 |
| SGF |
2018 |
Using Predictive Analytics to Improve a Student Advising System |
Thanuja Sakruti,
Youyou Zheng |
source |
13 |
| SGF |
2018 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at USPS |
Olayemi Olatunji |
source |
7 |
| SGF |
2018 |
Using SAS OnDemand for Academics: Ten Tips for Success |
Randy Mullis |
source |
11 |
| SGF |
2018 |
Using SAS to Teach Credit Risk: From Undergraduate Studies to Professional Education [presentation] |
Cristian Bravo |
source |
25 |
| SESUG |
2017 |
Analysis of Tweets on Demonetization in India using SAS Enterprise Miner |
Jital Patel,
Narmada Deve Panneerselvam |
source |
19 |
| SESUG |
2017 |
Finding the Gold in Your Data: An Overview of Data Mining |
David A. Dickey |
source |
25 |
| SESUG |
2017 |
From Words to Actions: Using Text Analytics to Drive Business Decisions |
Reid Baughman |
source |
6 |
| SESUG |
2017 |
Identifying Semantically Equivalent Questions Using Singular Value Decomposition |
Varsha Reddy Akkaloori |
source |
7 |
| SESUG |
2017 |
Understanding the influence of the day of the week in the reviews written using SAS Enterprise Miner TM and SAS Sentiment Analysis Studio |
Sujal Reddy Alugubelli |
source |
10 |
| SESUG |
2017 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at the U.S. Postal Service |
Olayemi Olatunji,
United States Postal |
source |
7 |
| SCSUG |
2017 |
Analysis of the effects of financial parameters on GDP and poverty using panel data analysis. |
Akshay Arora |
source |
13 |
| SCSUG |
2017 |
Analysis on EpiPen Tweets during Crisis Situations |
Goutam Chakraborty,
Miriam McGaugh,
Josh Weiner |
source |
14 |
| SCSUG |
2017 |
Analyzing Theft Occurrences in Chicago Using SAS Enterprise Miner 14.1 |
Shikha Prasad,
Kunal Parekh,
Goutam Chakraborty,
Miriam McGaugh |
source |
10 |
| SCSUG |
2017 |
Apple or Samsung? Which Phone Should I Buy? Sentiment Analysis Utilizing Customer Reviews on Unlocked iPhone and Samsung Galaxy |
Rosie Nguyen,
Nandan Moza,
Goutam Chakraborty,
Miriam McGaugh |
source |
14 |
| SCSUG |
2017 |
Classifying and Predicting Spam Messages Using Text Mining in SAS Enterprise Miner |
Venkata Kondamudi,
Sai Mounika,
Balamurugan Mohan |
source |
14 |
| SCSUG |
2017 |
Enhancement of Clinical Decision Making Using Predictive Modeling |
Archana Chinnaswamy |
source |
9 |
| SCSUG |
2017 |
Prediction of Used Cars? Prices by Using SAS EM |
Jaideep Muley,
Vijay Kumar Movva |
source |
12 |
| SCSUG |
2017 |
Predictive Analysis for Classifying Type 2 Diabetes Patients Using SAS Enterprise Miner 14.1 and SAS Enterprise Guide 7.1 |
Saurabh Sanjayrao Kokad |
source |
10 |
| SCSUG |
2017 |
Sentiment Analysis on YouTube Movie Trailer Comments to Determine the Impact on Box-Office Earnings |
Rishanki Jain |
source |
9 |
| SCSUG |
2017 |
Text Mining on Donor's Conversation with Solicitors |
Harsh Gupta |
source |
12 |
| SCSUG |
2017 |
Use Machine Learning to Discover Your Rules |
David R. Duling |
source |
10 |
| SCSUG |
2017 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at the U.S. Postal Service |
Olayemi Olatunji |
source |
8 |
| SCSUG |
2017 |
Which smartphone would you choose? |
Mohana Krishna Chaitanya Korlepara,
Miriam McGaugh,
Goutam Chakraborty |
source |
15 |
| PHUSE EU |
2017 |
Metadata-driven Tool for Creation of a Dataset for Exploratory Analyses |
Alexey Kuznetsov |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Topology-based Clinical Data Mining: Identifying Hidden Patterns in Clinical Datasets |
Sergey Glushakov |
source
presentation source |
18 |
| MWSUG |
2017 |
Claim Analytics |
Mei Najim |
|
18 |
| WUSS |
2017 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at the U.S. Postal Service |
Olayemi Olatunji |
source |
7 |
| PharmaSUG |
2017 |
Tips and Best Practices using SAS Analytics |
Tho H. Nguyen,
Paul Segal |
source |
7 |
| PharmaSUG |
2017 |
Topology-based Clinical Data Mining for Discovery of Hidden Patterns in Multidimensional Data |
Sergey Glushakov,
Iryna Kotenko,
Andrey Rekalo |
source |
20 |
| SGF |
2017 |
A Big-Data Challenge: Visualizing Social Media Trends about Cancer Using SAS Text Miner |
Scott Koval,
Yijie Li,
Mia Lyst |
source |
8 |
| SGF |
2017 |
A Data Mining Approach to Predict Students at Risk |
Youyou Zheng,
Thanuja Sakruti |
source |
13 |
| SGF |
2017 |
A Hadoop Journey along the SAS Road |
Sumit Sukhwani,
Krutharth Peravalli,
Amit Gautam |
source |
8 |
| SGF |
2017 |
Am I Getting the Most Value out of My SAS Installation Dollars? |
Al Cordoba |
source |
7 |
| SGF |
2017 |
An Information Technology Perspective of SAS at The University of Memphis |
Robert Jackson |
source |
8 |
| SGF |
2017 |
Building Bayesian Network Classifiers Using the HPBNET Procedure |
Ye Liu,
Weihua Shi,
Wendy Czika |
source |
19 |
| SGF |
2017 |
Classroom Success with SAS Grid Manager and SAS Visual Analytics: Coping With Big Data |
John Jernigan,
Ken Gahagan,
Cheryl Doninger |
source |
11 |
| SGF |
2017 |
Construction of a Disease Network and a Prediction Model for Dementia |
Jinwoo Cho |
source |
14 |
| SGF |
2017 |
Developing a Product Recommendation Platform for Real-Time Decisions in the Direct Sales Environment |
Francisco Pigato |
source |
7 |
| SGF |
2017 |
Developing Your Own SAS Studio Custom Tasks for Advanced Analytics |
Elliot Inman,
Olivia Wright |
source |
20 |
| SGF |
2017 |
Enabling Advanced Customer Value Management with SAS |
Noorulain Malik |
source |
7 |
| SGF |
2017 |
Enhancing Customer Experience through Text Analysis of Survey Comments |
Vinoth Kumar Raja,
Sumit Sukhwani,
Dmitriy Khots |
source |
8 |
| SGF |
2017 |
Examining Higher Education Performance Metrics with SAS Enterprise Miner and SAS Visual Analytics |
Taylor Blaetz,
Tuesdi Helbig,
Gina Huff,
Matt T. Bogard |
source |
15 |
| SGF |
2017 |
Fuzzy Matching and Predictive Models for Acquisition of New Customers |
Daniel Marinescu |
source |
12 |
| SGF |
2017 |
Getting Started with Designing and Implementing a SAS 9.4 Metadata and File System Security Design |
Philip Hopkins |
source |
20 |
| SGF |
2017 |
Getting the Latest and Greatest from SAS 9.4: Best Practices for Upgrades and Migrations |
Jamie Williams |
source |
13 |
| SGF |
2017 |
How Members Really Feel About Your Credit Card |
Anirban Chakraborty,
Surya Bhaskar Ayyalasomayajula |
source |
25 |
| SGF |
2017 |
KA Team: Crime in the City of Philadelphia |
Edwin Baidoo,
Christina Jones,
Muniza Naqvi |
source |
21 |
| SGF |
2017 |
Methods of Multinomial Classification Using Support Vector Machines |
Ralph Abbey,
Taiping He,
Tao Wang |
source |
20 |
| SGF |
2017 |
Mind-Map the Gap: Sentiment Analysis of Public Transport |
Tamas Bosznay |
source |
20 |
| SGF |
2017 |
Modeling the Merchandise Return Behavior of Anonymous and Non-Anonymous Online Apparel Retail Shoppers |
Sunny Lam |
source |
20 |
| SGF |
2017 |
Open Your Mind: Use Cases for SAS and Open-Source Analytics |
Tuba Islam |
source |
10 |
| SGF |
2017 |
Optimization of Interactive Voice Response Systems Using SAS |
Padmashri Janarthanam,
Vinoth Kumar Raja |
source |
6 |
| SGF |
2017 |
Optimizing Anti-Money Laundering Transaction Monitoring Systems Using SAS Analytical Tools |
Stephen M. Overton,
Eric Hale,
Leigh Ann Herhold |
source |
10 |
| SGF |
2017 |
Outline Outliers: Adding a Business Sense |
Alex Glushkovsky |
source |
17 |
| SGF |
2017 |
Predicting the Completeness of Clinical Data through Claims Data Matching Using SAS Enterprise Miner [presentation] |
Catherine Olson,
Thomas Horstman |
source |
7 |
| SGF |
2017 |
Property and Casualty Insurance Predictive Analytics in SAS |
Mei Najim |
source |
17 |
| SGF |
2017 |
Random Forests with Approximate Bayesian Model Averaging |
Tiny Du Toit,
Andre De Waal |
source |
11 |
| SGF |
2017 |
Real AdaBoost: Boosting for Credit Scorecards and Similarity to WOE Logistic Regression |
Paul Edwards |
source |
12 |
| SGF |
2017 |
Temporal Text Mining: A Thematic Exploration of Don Quixote |
Ray Wright |
source |
16 |
| SGF |
2017 |
Text Mining of Movie Synopsis by SAS Enterprise Miner |
Yiyun Zhou |
source
pdf |
3 |
| SGF |
2017 |
Understanding SAS Embedded Process with Hadoop Security |
David Ghazaleh |
source |
16 |
| SGF |
2017 |
Use Machine Learning to Discover Your Rules |
David R. Duling |
source |
10 |
| SGF |
2017 |
Using Graph Analytics for Predictive Modeling in Life Insurance |
Robert G. Moore |
source |
6 |
| SGF |
2017 |
Using SAS to Analyze Emergency Department Visits: Medicaid Patients Compared to Other Pay Sources |
Bradley Casselman,
Taylor K. Larkin,
Denise J. McManus |
source |
16 |
| SGF |
2017 |
Using Text Analysis to Improve the Quality of Scoring Models with SAS Enterprise Miner |
Piotr Małaszek |
source |
11 |
| SGF |
2017 |
War and Peace: SAS Platform Support. Can We Make It Easier? |
Sergey Iglov |
source |
12 |
| SCSUG |
2016 |
Analyzing sentiments in tweets for Tesla Model 3 |
Praneth Guggilla,
Tejaswi Jha,
Goutam Chakraborty |
source |
12 |
| SCSUG |
2016 |
Contextualized Market Basket Analysis - How to learn more from your Point of Sale Data in Base SAS and SAS Enterprise Miner |
Andrew A. Kramer |
|
11 |
| SCSUG |
2016 |
Determining the functionality of Water Pumps in Tanzania Using SAS EM and VA |
Indra Kiran Chowdavarapu,
Vivek Damodaran Manikandan |
source |
9 |
| SCSUG |
2016 |
Enabling news trading by automatic categorisation of news articles |
Praveen Kumar Kotekal,
Vishwanath Kolar Bhaskara |
source |
9 |
| SCSUG |
2016 |
Hybrid recommendation system to provide suggestions based on user reviews |
Shanmugavel Gnanasekar,
Ravi Shankar Subramanian |
source |
10 |
| SCSUG |
2016 |
Optimize the Domestic Air Traffic System of United States using SAS Enterprise Miner |
G. Piyush,
Anuj Dwivedi,
Aditya Agrawal |
source |
16 |
| SESUG |
2016 |
A Data Mining Approach to Predict Student-at-risk |
Youyou Zheng,
Thanuja Sakruti,
Abhishek Uppalapati,
Sivakumar Jaganathan |
source |
12 |
| SESUG |
2016 |
Empowering Self-Service Capabilities with Agile Analytics |
Paul Segal,
Tho H. Nguyen,
Bob Matsey |
source |
8 |
| SESUG |
2016 |
Know your Interest Rate |
Anirban Chakraborty,
Goutam Chakraborty |
source |
16 |
| SESUG |
2016 |
Text Analysis of American Airline s Customer Reviews |
Rajesh Tolety |
source |
7 |
| SESUG |
2016 |
Text mining and sentiment analysis on video game user reviews using SAS Enterprise Miner |
Mukesh Kumar Singh,
Nikhil Batti,
Miriam McGaugh |
source |
13 |
| SESUG |
2016 |
The Orange Lifestyle |
Sangar Rane,
Mohit Singhi |
source |
10 |
| MWSUG |
2016 |
An Animated Guide: Deep Neural Networks in SAS Enterprise Miner |
Russell M. Lavery |
|
47 |
| MWSUG |
2016 |
An Introduction to the HPFOREST Procedure and its Options |
Carl Nord,
Jacob Keeley |
|
12 |
| MWSUG |
2016 |
Analyzing sentiments in tweets for Tesla Model 3 using SAS Enterprise Miner and SAS Sentiment Analysis Studio |
Tejaswi Jha,
Praneth Guggilla |
|
12 |
| MWSUG |
2016 |
Discover the golden paths, unique sequences and marvelous associations out of your big data using Link Analysis in SAS Enterprise Miner TM |
Delali Agbenyegah,
Candice Zhang |
|
14 |
| MWSUG |
2016 |
Hybrid recommendation system to provide suggestions based on user reviews |
Ravi Shankar Subramanian,
Shanmugavel Gnanasekar |
|
10 |
| MWSUG |
2016 |
Property and Casualty Insurance Predictive Analytics in SAS |
Mei Najim |
|
17 |
| MWSUG |
2016 |
Weight of Evidence Coding and Binning of Predictors in Logistic Regression |
Bruce S. Lund |
|
16 |
| WUSS |
2016 |
An Animated Guide: Incremental Response Modeling in Enterprise Miner |
Russell M. Lavery |
source |
19 |
| WUSS |
2016 |
Clinton vs. Trump 2016: Analyzing and Visualizing Tweets and Sentiments of Hillary Clinton and Donald Trump |
Siddharth Grover |
source |
9 |
| WUSS |
2016 |
Descriptive Analysis of Donation Amount Data and Text Mining of Tweets on Presidential Primaries using SAS |
Aditya Jakkam,
Swetha Nallamala |
source |
14 |
| WUSS |
2016 |
Social Media, Anonymity, and Fraud: HP Forest Node in SAS Enterprise Miner |
Taylor K. Larkin,
Denise J. McManus |
source |
5 |
| WUSS |
2016 |
Text Analysis of American Airline s Customer Reviews |
Saurabh Choudhary,
Rajesh Tolety |
source |
9 |
| WUSS |
2016 |
Using Shared Accounts in Kerberized Hadoop Clusters with SAS: How Can I Do That? |
Michael Shealy |
source |
11 |
| SGF |
2016 |
A Property and Casualty Insurance Predictive Modeling Process in SAS |
Mei Najim |
source |
14 |
| SGF |
2016 |
An Efficient Pattern Recognition Approach with Applications |
Patrick Hall,
Jorge Silva,
Ilknur Kaynar Kabul,
Keith R. Holdaway,
Alex Chien |
source |
9 |
| SGF |
2016 |
Analysis of IMDb Reviews for Movies and Television Series Using SAS Enterprise Miner and SAS Sentiment Analysis Studio |
Ameya Jadhavar,
Goutam Chakraborty,
Prithvi Raj Sirolikar |
source |
17 |
| SGF |
2016 |
Analytics and Data Management in a Box: Dramatically Increase Performance |
Greg Otto,
Tho H. Nguyen,
Paul Segal |
source |
14 |
| SGF |
2016 |
Application of Data Mining Techniques in Improving Breast Cancer Diagnosis |
Josephine Akosa |
source
presentation |
10 |
| SGF |
2016 |
Application of Gradient Boosting through SAS Enterprise Miner to Classify Human Activities |
Minh Pham,
Mary Ruppert-Stroescu,
Mostakim Tanjil |
source
presentation |
8 |
| SGF |
2016 |
Arrest Prediction and Analysis based on a Data Mining Approach |
Karan Rudra,
Goutam Chakraborty,
Maitreya Kadiyala |
source |
9 |
| SGF |
2016 |
Classifying Fatal Automobile Accidents in the US, 2010-2013: Using SAS Enterprise Miner to Understand and Reduce Fatalities |
Catherine LaChapelle,
Daniel Brannock,
Aric LaBarr,
Craig Shaver |
source |
11 |
| SGF |
2016 |
Debt Collection through the Lens of SAS Analytics |
Karush Jaggi,
Harold Dickerson,
Thomas Waldschmidt |
source
presentation |
11 |
| SGF |
2016 |
Diagnosing Obstructive Sleep Apnea: Using Predictive Analytics Based on Wavelet Analysis in SAS/IML Software and Spectral Analysis in PROC SPECTRA |
Woranat Wongdhamma |
source |
12 |
| SGF |
2016 |
Easier Platform Administration using SAS 9.4 Grid Options Sets |
Andrew Howell |
source |
10 |
| SGF |
2016 |
Ensemble Modeling: Recent Advances and Applications |
Wendy Czika,
Ye Liu |
source |
20 |
| SGF |
2016 |
Ensuring that Your SAS Infrastructure Is Able to Meet Your SAS Users' Demands |
Margaret A. Crevar |
source |
11 |
| SGF |
2016 |
Exploring SAS Embedded Process Technologies on Hadoop |
David Ghazaleh |
source |
17 |
| SGF |
2016 |
Exploring the Factors That Impact Injury Severity Using Hierarchical Linear Modeling (HLM) |
Pradeep Bista |
source |
9 |
| SGF |
2016 |
From Sensors to Solutions: An Example of Analytics in Motion |
Milad Falahi,
Gilbert Hernandez |
source |
12 |
| SGF |
2016 |
Improve Your Business through Process Mining |
Emily Y. Gao,
Robert Chu,
Xudong Sun |
source |
17 |
| SGF |
2016 |
Improving Performance of Memory-Based Reasoning Model by Using Weight of Evidence Coded Categorical Variables |
Vinoth Kumar Raja,
Goutam Chakraborty,
Vignesh Dhanabal |
source |
6 |
| SGF |
2016 |
Introducing SAS Grid Manager for Hadoop |
Cheryl Doninger,
Doug Haigh |
source |
10 |
| SGF |
2016 |
Kerberos Delegation with SAS 9.4 |
Stuart J. Rogers |
source |
19 |
| SGF |
2016 |
Lyric Complexity and Song Popularity: Analysis of Lyric Composition and Relation among Billboard Top 100 Songs |
John Harden,
Yang Gao,
Vojtech Hrdinka,
Chris Linn |
source |
15 |
| SGF |
2016 |
Measuring Brand Sentiment Using Smileys |
Sharat Dwibhasi |
source |
8 |
| SGF |
2016 |
Predicting Forest Fire Occurrence and Incremental Fire Rate Using SAS 9.4 and SAS Enterprise Miner 14.1 |
Quyen Nguyen |
source |
12 |
| SGF |
2016 |
Predicting If Mental Health Facilities Will Offer Free Treatment to Patients Who Cannot Afford It |
Ram Poudel,
Lynn Xiang |
source |
11 |
| SGF |
2016 |
Predicting Rare Events Using Specialized Sampling Techniques in SAS |
Rhupesh Damodaran Ganesh Kumar,
Kiren Raj Mohan Jagan Mohan |
source |
7 |
| SGF |
2016 |
Prescriptive Analytics - Providing the Instruction to Do What's Right |
Tho H. Nguyen,
Fiona McNeill |
source
presentation |
11 |
| SGF |
2016 |
Reducing and Screening Redundant Variables in Logistic Regression Models Using SAS/STAT Software and SAS Enterprise Miner |
Xinghe Lu |
source |
10 |
| SGF |
2016 |
SAS Grid Architecture Solution Using IBM Hardware |
Whayne Rouse,
Andrew Scott |
source |
11 |
| SGF |
2016 |
Streaming Decisions: How SAS Puts Streaming Data to Work |
Fiona McNeill,
David R. Duling,
Steve Sparano |
source
zip |
15 |
| SGF |
2016 |
Survival Analysis of the Patients Diagnosed with Non-Small Cell Lung Cancer Using SAS Enterprise Miner 13.1 |
Raja Rajeswari Veggalam,
Akansha Gupta,
Goutam Chakraborty |
source |
11 |
| SGF |
2016 |
Text Analytics and Assessing Patient Satisfaction [presentation] |
Divya Sridhar |
source
presentation |
5 |
| SGF |
2016 |
Text Analytics and Brand Topic Maps |
Nicholas Evangelopoulos |
source |
11 |
| SGF |
2016 |
Tips and Best Practices for Configuring Integrated Windows Authentication |
Mike Roda |
source |
18 |
| MWSUG |
2015 |
A Property & Casualty Insurance Predictive Modeling Process in SAS |
Mei Najim |
|
14 |
| MWSUG |
2015 |
Debt Collection Through SAS Analytics Lens |
Karush Jaggi,
Thomas Waldschmidt,
Harold Dickerson,
Eric Hayes,
Goutam Chakraborty |
|
11 |
| MWSUG |
2015 |
Get the highest bangs for your marketing bucks using Incremental Response Models in SAS Enterprise Miner |
Delali Agbenyegah |
|
8 |
| MWSUG |
2015 |
Using Enterprise Miner to Create Model Documentation And/or Reproducible Research |
Rex Pruitt |
|
11 |
| PHUSE EU |
2015 |
Hands-on Data Mining, Digging up clinicaltrials.gov Data with SAS 9 |
Mahdi About |
source |
12 |
| SESUG |
2015 |
How to be a Data Scientist Using SAS |
Charles D. Kincaid,
Experis Business |
source |
13 |
| WUSS |
2015 |
Application of Data Mining in Energy Industry: A Case Study of NOx Prediction |
Jongsawas Chongwatpol |
source |
9 |
| WUSS |
2015 |
The breakthrough of SAS University Edition: What is it and how do I get it? |
Chelsea Lofland |
source |
4 |
| PharmaSUG CN |
2015 |
Configuring SAS Business Intelligence (BI) client with the SAS server to support multilingual data |
Wei Zheng |
|
13 |
| SGF |
2015 |
A Case Study: Improve Classification of Rare Events with SAS Enterprise Miner |
Ruizhe Wang,
Novik Lee,
Yun Wei |
source
zip |
12 |
| SGF |
2015 |
Alien Nation: Text Analysis of UFO Sightings in the US Using SAS Enterprise Miner 13.1 |
Pradeep Reddy Kalakota,
Naresh Abburi,
Goutam Chakraborty,
Zabiulla Mohammed |
source
zip |
14 |
| SGF |
2015 |
Analyzing and Visualizing the Sentiment of the Ebola Outbreak via Tweets |
Dheeraj Jami,
Goutam Chakraborty,
Shivkanth Lanka |
source |
11 |
| SGF |
2015 |
Analyzing Customer Answers in Calls from Collections Using SAS Text Miner to Respond in an Efficient and Effective Way |
Oscar Ayala,
Jenny Lancheros |
source |
6 |
| SGF |
2015 |
Analyzing Direct Marketing Campaign Performance Using Weight of Evidence Coding and Information Value through SAS Enterprise Miner Incremental Response |
Sravan Vadigepalli |
source
zip |
9 |
| SGF |
2015 |
Applied Analytics in Festival Tourism: A Case Study of Intention-to-Revisit Prediction in an Annual Local Food Festival in Thailand |
Jongsawas Chongwatpol,
Thanathorn Vajirakachorn |
source |
13 |
| SGF |
2015 |
Clustering Techniques to Uncover Relative Pricing Opportunities: Relative Pricing Corridors Using SAS Enterprise Miner and SAS Visual Analytics |
Ryan K. Carr,
Charles Park |
source |
8 |
| SGF |
2015 |
Credit Scorecard Generation Using the Credit Scoring Node in SAS Enterprise Miner [presentation] |
Ayush Priyadarshi,
Kushal Kathed,
Shilpi Prasad |
source |
3 |
| SGF |
2015 |
Determining the Key Success Factors for Hit Songs in the Billboard Music Charts |
Piboon Banpotsakun,
Jongsawas Chongwatpol |
source |
12 |
| SGF |
2015 |
Discovering Personality Type through Text Mining in SAS Enterprise Miner 12.3 [presentation] |
Mark L. Schneider,
Andrew Van Der Werff |
source |
7 |
| SGF |
2015 |
Donor Sentiment and Characteristic Analysis Using SAS Enterprise Miner and SAS Sentiment Analysis Studio |
Ramcharan Kakarla,
Goutam Chakraborty |
source |
12 |
| SGF |
2015 |
Drilling for Deepwater Data: A Forensic Analysis of the Gulf of Mexico Deepwater Horizon Disaster |
Jim Duarte,
Keith R. Holdaway,
Moray Laing |
source |
8 |
| SGF |
2015 |
Educating Future Business Leaders in the Era of Big Data |
Tonya E. Balan |
source |
8 |
| SGF |
2015 |
Gross Margin Percent Prediction: Using the Power of SAS Enterprise Miner 12.3 to Predict the Gross Margin Percent for a Steel Manufacturing Company [presentation] |
Kushal Kathed,
Patti Jordan,
Ayush Priyadarshi |
source |
3 |
| SGF |
2015 |
How to Use Internal and External Data to Realize the Potential for Changing the Game in Handset Campaigns |
Hurcan Coskun |
source |
8 |
| SGF |
2015 |
Important Things to Know when Deploying SAS Grid Manager |
Doug Haigh,
Glenn Horton |
source |
5 |
| SGF |
2015 |
Improving the Performance of Data Mining Models with Data Preparation Using SAS Enterprise Miner |
Ricardo Galante |
source |
21 |
| SGF |
2015 |
Improving the Performance of Two-Stage Modeling Using the Association Node of SAS Enterprise Miner 12.3 |
Girish Shirodkar,
Goutam Chakraborty,
Ankita Chaudhari |
source |
9 |
| SGF |
2015 |
Killing Them with Kindness: Policies Not Based on Data Might Do More Harm Than Good |
Tuesdi Helbig,
Matthew Foraker |
source |
22 |
| SGF |
2015 |
Methodology of Model Creation |
Peter Kertys |
source |
11 |
| SGF |
2015 |
Modeling to Improve the Customer Unit Target Selection for Inspections of Commercial Losses in the Brazilian Electric Sector: The case of CEMIG |
Sergio Henrique Ribeiro,
Iguatinan Monteiro |
source |
7 |
| SGF |
2015 |
Next Generation: Using SAS Decision Manager to Modernize and Improve Your Operational Decisions |
Steve Sparano |
source |
20 |
| SGF |
2015 |
Predicting Readmission of Diabetic Patients Using the High-Performance Support Vector Machine Algorithm of SAS Enterprise Miner 13.1 |
Hephzibah Munnangi,
Goutam Chakraborty |
source |
10 |
| SGF |
2015 |
SAS and SAP Business Warehouse on SAP HANA--What's in the Handshake? |
Tatyana Petrova |
source |
17 |
| SGF |
2015 |
SAS Does Data Science: How to Succeed in a Data Science Competition |
Patrick Hall |
source
zip |
11 |
| SGF |
2015 |
Text Mining Kaiser Permanente Member Complaints with SAS Enterprise Miner [presentation] |
Amanda Pasch |
source |
5 |
| SGF |
2015 |
The More Trees, the Better! Scaling Up Performance Using Random Forest in SAS Enterprise Miner |
Narmada Deve Panneerselvam |
source |
10 |
| SGF |
2015 |
Time to Harvest: Operationalizing SAS Analytics on the SAP HANA Platform |
Morgen Christoph |
source |
11 |
| SGF |
2015 |
To Believe or Not To Believe? The Truth of Data Analytics Results [presentation] |
Mike Hardin |
source |
71 |
| SGF |
2015 |
Unconventional Data-Driven Methodologies Forecast Performance in Unconventional Oil and Gas Reservoirs |
Keith R. Holdaway,
Louis Fabbi,
Dan Lozie |
source |
20 |
| SGF |
2015 |
Understanding Characteristics of Insider Threats by Using Feature Extraction |
Ila Gokarn,
Clifton Phua |
source |
14 |
| SGF |
2015 |
Unstructured Data Mining to Improve Customer Experience in Interactive Voice Response Systems |
Dmitriy Khots |
source |
11 |
| SGF |
2015 |
Using SAS Enterprise Guide, SAS Enterprise Miner, and SAS Marketing Automation to Make a Collection Campaign Smarter |
Darwin A. Amezquita,
Paulo Fuentes,
Andres F. Gonzalez |
source |
9 |
| SGF |
2015 |
Using SAS Enterprise Miner to Predict Breast Cancer at an Early Stage |
Gibson Ikoro,
Beatriz de la Iglesia |
source |
9 |
| SGF |
2015 |
Using SAS to Combine Regression and Time Series Analysis on U.S. Financial Data to Predict the Economic Downturn |
Avinash Kalwani,
Nishant Vyas |
source |
6 |
| SGF |
2015 |
Using SAS to Deliver Web Content Personalization Using Cloud-Based Clickstream Data and On-premises Customer Data |
Mahesh Subramanian,
Suneel Grover |
source |
24 |
| SGF |
2015 |
Using Text from Repair Tickets of a Truck Manufacturing Company to Predict Factors that Contribute to Truck Downtime |
Ayush Priyadarshi,
Goutam Chakraborty |
source |
9 |
| SGF |
2015 |
When Two Are Better Than One: Fitting Two-Part Models Using SAS |
Laura Kapitula |
source |
9 |
| SESUG |
2014 |
Dashboards with SAS Visual Analytics |
Patricia S. Aanderud,
Michelle Homes |
source |
20 |
| SESUG |
2014 |
Techniques in Processing Data on Hadoop |
Douglas B. Liming |
source |
11 |
| SESUG |
2014 |
Text Analytics using High Performance SAS Text Miner |
Edward R. Jones |
source |
7 |
| MWSUG |
2014 |
Analyzing Collection Effectiveness using Incremental Response Modeling |
Ryan Burton |
|
7 |
| MWSUG |
2014 |
Conquering Big Data Analytics with SAS, Teradata and Hadoop |
John Cunningham,
Tho H. Nguyen,
Paul Segal |
|
10 |
| MWSUG |
2014 |
SAS In-Database Analytics for Teradata: Stop the Data Movement |
Paul Segal,
Tho H. Nguyen,
John Cunningham |
|
4 |
| MWSUG |
2014 |
So You Want to be SAS Certified |
Ben Cochran |
|
10 |
| MWSUG |
2014 |
Text Analytics in High Performance SAS and SAS Enterprise Miner |
Edward R. Jones |
|
16 |
| PharmaSUG CN |
2014 |
From Coal Mining to Data Mining: Advancing Programming Management for Clinical Projects with Text Analytics |
Zhouming Sun |
|
10 |
| WUSS |
2014 |
Conquering Big Data Analytics Challenges with SAS, Teradata and Hadoop |
Tho H. Nguyen,
Paul Segal,
John Cunningham |
source |
10 |
| WUSS |
2014 |
Expediting Access to Critical Pathology Data |
Leanne Goldstein,
Rebecca Ottesen,
Julie A. Kilburn,
Joyce C. Niland |
source |
8 |
| WUSS |
2014 |
SAS In-Database Analytics for Teradata: Stop the Data Movement |
Tho H. Nguyen,
Paul Segal |
source |
4 |
| PharmaSUG |
2014 |
Clinical Trial Data Integration: The Strategy, Benefits, and Logistics of Integrating Across a Compound |
Natalie Reynolds,
Keith Hibbetts |
source |
12 |
| PharmaSUG |
2014 |
Expediting Access to Critical Pathology Data |
Rebecca Ottesen,
Leanne Goldstein,
Julie A. Kilburn,
Joyce C. Niland |
source |
8 |
| PharmaSUG |
2014 |
Healthcare Data Manipulation and Analytics Using SAS |
Lumin Shen,
Jane Lu |
source |
11 |
| SGF |
2014 |
A Guide to SAS for the IT Organization |
Lisa Ann Horwitz |
source |
5 |
| SGF |
2014 |
An Overview of Machine Learning with SAS Enterprise Miner |
Patrick Hall,
Jared Dean,
Ilknur Kaynar Kabul,
Jorge Silva |
source
zip |
24 |
| SGF |
2014 |
Association Mining of Brain Data: An EEG Study |
Pankush Kalgotra,
Ramesh Sharda,
Goutam Chakraborty |
source |
6 |
| SGF |
2014 |
Automatic Detection of Section Membership for SAS Conference Paper Abstract Submissions: A Case Study |
Goutam Chakraborty,
Murali Krishna Pagolu |
source |
13 |
| SGF |
2014 |
Big Digital Data, Analytic Visualization, and the Opportunity of Digital Intelligence |
Suneel Grover |
source |
17 |
| SGF |
2014 |
Clustering and Predictive Modeling of Patient Discharge Records with SAS Enterprise Miner |
Linda Schumacher,
Goutam Chakraborty |
source |
9 |
| SGF |
2014 |
Customer Perception and Reality: Unraveling the Energy Customer Equation |
Mark Konya,
Kathy Ball |
source |
11 |
| SGF |
2014 |
Detecting Patterns Using Geo-Temporal Analysis Techniques in Big Data [presentation] |
Richard W. La Valley,
Abraham Usher,
Donald J. Henderson,
Paul M. Dorfman |
source |
1 |
| SGF |
2014 |
Disease Prevention to Reduce New Hampshire Health-Care Claims and Costs: A Data Mining Approach [presentation] |
Rakesh Karn,
Rom Khattri,
Pradeep Podila,
Linda Schumacher |
source |
6 |
| SGF |
2014 |
Doubling Down on Analytics: Using Analytic Results from Other Departments to Enhance Your Approach to Marketing |
Natalie G. Osborn,
Eric Peterson |
source |
6 |
| SGF |
2014 |
Empowering SAS Users on the SAP HANA Platform |
Christoph Morgen |
source |
9 |
| SGF |
2014 |
From Providing Support to Driving Decisions: Improving the Value of Institutional Research |
Tuesdi Helbig,
Gina Huff |
source |
8 |
| SGF |
2014 |
Graphs Useful for Variable Selection in Predictive Modeling |
Bob Moore |
source |
9 |
| SGF |
2014 |
How SAS and Teradata Dramatically Improve Data Analysis at CMS |
Richard Andrews |
source |
11 |
| SGF |
2014 |
How to be a Data Scientist Using SAS |
Chuck Kincaid |
source |
13 |
| SGF |
2014 |
Improving the Thermal Efficiency of Coal-Fired Power Plants: A Data Mining Approach |
Thanrawee Phurithititanapong,
Jongsawas Chongwatpol |
source |
12 |
| SGF |
2014 |
Internet Gambling Behavioral Markers: Using the Power of SAS Enterprise Miner 12.1 to Predict High-Risk Internet Gamblers |
Sai Vijay Kishore Movva,
Vandana Reddy,
Goutam Chakraborty |
source |
11 |
| SGF |
2014 |
Introduction to SAS Decision Management |
Steve Sparano,
Charlotte Crain,
David R. Duling |
source |
18 |
| SGF |
2014 |
Leveraging Ensemble Models in SAS Enterprise Miner |
Miguel M. Maldonado,
Jared Dean,
Wendy Czika,
Susan Haller |
source |
15 |
| SGF |
2014 |
Medical Scoring for Breast Cancer Recurrence |
Nurul Husna Jamian,
Yap Bee Wah,
Nor Aina Emran |
source |
13 |
| SGF |
2014 |
Migrating SAS Java EE Applications from WebLogic, WebSphere, and JBoss to Pivotal tc Server |
Zhiyong Li,
Alec S. Fernandez |
source |
12 |
| SGF |
2014 |
Predicting a Child Smoker Using SAS Enterprise Miner 12.1 [presentation] |
Jin Ho Jung,
Gaurav Pathak,
Goutam Chakraborty |
source |
3 |
| SGF |
2014 |
Queues for Newbies . How to Speak LSF in a SAS World |
Andrew Howell |
source |
9 |
| SGF |
2014 |
Reevaluating Policy and Claims Analytics: A Case of Corporate Fleet and Non-Fleet Customers in the Automobile Insurance Industry |
Kittipong Trongsawad,
Jongsawas Chongwatpol |
source |
10 |
| SGF |
2014 |
Researching Individual Credit Rating Models |
Colin Nugteren |
source |
12 |
| SGF |
2014 |
SAS Admins Need a Dashboard, Too |
Patricia S. Aanderud,
Michelle Homes |
source |
20 |
| SGF |
2014 |
SAS Data Mining for Predictor Identification: Developing Strategies for High School Dropout Prevention |
Wendy B. Dickinson,
Morgan C. Wang |
source |
9 |
| SGF |
2014 |
SAS Predictive Asset Maintenance: Find Out Why Before It's Too Late! |
George S. Habek |
source |
19 |
| SGF |
2014 |
So Much Software, So Little Time: Deploying SAS Onto Oodles of Machines |
Mark L. Schneider |
source |
13 |
| SGF |
2014 |
Techniques in Processing Data on Hadoop |
Donna De Capite |
source |
11 |
| SGF |
2014 |
Text Analytics: Predicting the Success of Newly Released Free Android Apps Using SAS Enterprise Miner and SAS Sentiment Analysis Studio [presentation] |
Vandana Reddy,
Chinmay Dugar |
source |
3 |
| SGF |
2014 |
Text Mining Economic Topic Sentiment for Time Series Modeling |
Michael P. Dessauer,
Justin Kauhl |
source |
14 |
| SGF |
2014 |
The Role of Customer Response Models in Customer Solicitation Center's Direct Marketing Campaign |
Arun Mandapaka,
Amit Kushwah,
Goutam Chakraborty |
source |
12 |
| SGF |
2014 |
The Soccer Oracle: Predicting Soccer Game Outcomes Using SAS Enterprise Miner [presentation] |
Vandana Reddy,
Sai Vijay Kishore Movva |
source |
3 |
| SGF |
2014 |
Uncovering Trends in Research Using SAS Text Analytics with Examples from Nanotechnology and Aerospace Engineering |
Tom Sabo |
source |
16 |
| SGF |
2014 |
Using SAS Enterprise Miner to Predict the Injury Risk Involved in Car Accidents |
Prateek Khare,
Vandana Reddy,
Goutam Chakraborty |
source |
7 |
| SGF |
2014 |
What's New in SAS Enterprise Miner 13.1 |
Jared Dean,
Jonathan Wexler |
source |
16 |
| SGF |
2014 |
Wow, I Could Have Had a VA! - A Comparison Between SAS Visual Analytics and Other SAS Products |
Brian K. Varney |
source |
7 |
| WUSS |
2013 |
How to be a Data Scientist Using SAS |
Chuck Kincaid |
source |
13 |
| SESUG |
2013 |
Explore RFM approaches using SAS |
Explore RFM |
source |
6 |
| SESUG |
2013 |
Finding the Gold in Your Data: An Overview of Data Mining |
David A. Dickey |
source |
16 |
| SESUG |
2013 |
Survey of Big Data Solutions using SAS Technologies |
Jack N. Shoemaker |
source |
3 |
| SESUG |
2013 |
What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs |
Satish Garla |
source |
15 |
| PHUSE EU |
2013 |
SAS Predictive and Visual Analytics: Software Demonstration [presentation] |
Andy Bayliss |
source |
9 |
| PHUSE EU |
2013 |
Utilising Data Warehousing to Validate Clinical Trial Projects and to Select and Recruit Patients [presentation] |
Tim Armitage |
source |
39 |
| MWSUG |
2013 |
Finding the Gold in Your Data: An Overview of Data Mining |
David A. Dickey |
|
16 |
| NESUG |
2013 |
An Animated Guide: An Introduction to Neural Nets: |
Russell M. Lavery |
|
12 |
| NESUG |
2013 |
How to be a Data Scientist Using SAS |
Chuck Kincaid |
|
13 |
| SGF |
2013 |
%GetReviews: A SAS Macro to Retrieve User Reviews in JSON Format from Review Websites and Create SAS Data Sets |
Ganesh Badisa,
Goutam Chakraborty,
Siddhartha Reddy Mandati |
source |
9 |
| SGF |
2013 |
A Data-Driven Analytic Strategy for Increasing Yield and Retention at Western Kentucky University Using SAS Enterprise BI and SAS Enterprise Miner |
Matt T. Bogard |
source |
12 |
| SGF |
2013 |
Be Customer Wise or Otherwise: Combining Data Mining and Interactive Visual Analytics to Analyze Large and Complex Customer Resource Management (CRM) Data |
Aditya Misra,
Junyao Ji,
Kam Tin Seong |
source |
11 |
| SGF |
2013 |
Bringing Churn Modeling Straight to the Source: SAS and Teradata In-Database Model Development |
Jonathan Wexler,
Karl Krycha |
source |
9 |
| SGF |
2013 |
Data Mining of U.S. Patents: Research Trends of Major Technology Companies |
Ken Potter,
Robert N. Hatton |
source |
11 |
| SGF |
2013 |
Deciphering Emoticons for Text Analytics: A Macro-Based Approach |
Chad Atkinson |
source |
15 |
| SGF |
2013 |
Do People Still Miss Steve Jobs As the CEO of Apple Inc.? A Text Mining Approach: Comparing SAS and R |
Anurag G. Srivastava,
Pranav Karnavat |
source
pdf |
18 |
| SGF |
2013 |
Estimates of Personal Revenue from Credit and Sociodemographic Information Combining Decision Trees and Artificial Neural Networks (ANN) |
Deybis Florez Hormiga |
source |
4 |
| SGF |
2013 |
Extension Node to the Rescue of the Curse of Dimensionality via Weight of Evidence (WOE) Recoding |
Andrew Cathie,
Goutam Chakraborty,
Satish Garla |
source |
9 |
| SGF |
2013 |
Finding the Gold in Your Data: An Overview of Data Mining |
David A. Dickey |
source |
16 |
| SGF |
2013 |
Impact of London Olympics According to Tweeters |
Goutam Chakraborty,
Shirmeen Virji,
Yu Fu |
source
pdf |
7 |
| SGF |
2013 |
Incremental Response Modeling Using SAS Enterprise Miner |
Laura Ryan,
Ruiwen Zhang,
Taiyeong Lee,
Xiangxiang Meng |
source |
13 |
| SGF |
2013 |
Integrating SAS into Your Operational Environment: SOA: A Means to an End |
Rob Stephens,
Saravana Chandran |
source |
8 |
| SGF |
2013 |
Investigating the Impact of Amazon Kindle Fire HD 7? on Amazon.com Consumers Using SAS Text Miner and SAS Sentiment Analysis View Paper View Poster |
Goutam Chakraborty,
Hari Hara Sudhan Duraidhayalu,
Srihari Nagarajan |
source
pdf |
14 |
| SGF |
2013 |
Kerberos and SAS 9.4: A Three-Headed Solution for Authentication |
Stuart J. Rogers |
source |
15 |
| SGF |
2013 |
Leveraging Big Data Using SAS High-Performance Analytics Server |
Priya Sharma |
source |
9 |
| SGF |
2013 |
Predicting Application Review Rating with SAS Text Miner |
Jonghyun Kim,
Tianxi Dong,
Zhangxi Lin |
source
pdf |
8 |
| SGF |
2013 |
Predicting Women's Department Purchases in a Retail Store By Using the SEMMA Methodology |
Michael Soto |
source |
12 |
| SGF |
2013 |
Presenting Business Cases That Contain Complex, Technical Information to a Varied Audience |
Lori A. Guido,
Stephen Moore |
source
pdf |
5 |
| SGF |
2013 |
Replacing Manual Coding of Customer Survey Comments with Text Mining: A Story of Discovery with Textual Data in the Public Sector |
Jared Prins |
source |
19 |
| SGF |
2013 |
SAS Certification: Understand the Benefits of SAS Certification, Which SAS Certifications Are Available, and What SAS Certification Can Do for You |
Andrew Howell |
source |
9 |
| SGF |
2013 |
SAS Virtual Desktop Deployment at the U.S. Bureau of the Census |
Lori A. Guido,
Michael Bretz,
Stephen Moore |
source |
9 |
| SGF |
2013 |
The Forest and the Trees: See It All with SAS Visual Analytics Explorer |
Nascif Abousalh-Neto |
source |
14 |
| SGF |
2013 |
The Top Four User-Requested Grid Features Delivered with SAS Grid Manager 9.4 |
Doug Haigh |
source |
7 |
| SGF |
2013 |
Time Is Precious, So Are Your Models: SAS Provides Solutions to Streamline Deployment |
Jonathan Wexler,
Wayne Thompson |
source |
17 |
| SGF |
2013 |
Using Classification and Regression Trees (CART) in SAS Enterprise Miner? for Applications in Public Health |
Leonard Gordon |
source |
8 |
| SGF |
2013 |
Using Data Mining in Forecasting Problems |
Chip Wells,
Justin Kauhl,
Timothy Rey |
source |
17 |
| SGF |
2013 |
Using the Boosting Technique to Improve the Predictive Power of a Credit Risk Model |
Alejandro Correa Bahnsen,
Andres F. Gonzalez,
Darwin A. Amezquita |
source |
7 |
| SGF |
2013 |
Weathering the Storm: Using Predictive Analytics to Minimize Utility Outages |
Kathy Ball,
Mark Konya |
source
pdf |
10 |
| SGF |
2013 |
What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs |
Albert Hopping,
Rick Monaco,
Sarah Rittman,
Satish Garla |
source |
15 |
| SGF |
2013 |
What?s New in SAS Enterprise Business Intelligence for SAS 9.3 |
Rick Styll |
source |
24 |
| SGF |
2013 |
Where Should I Dig? What to Do Before Mining Your Data |
Stephanie R. Thompson |
source |
3 |
| NESUG |
2012 |
An Animated Guide: Regression Trees in JMP and Enterprise Miner |
Russell M. Lavery |
|
32 |
| PHUSE EU |
2012 |
JMP Clinical 4.0 [presentation] |
Valérie Nedbal |
source |
45 |
| SESUG |
2012 |
Evaluating effectiveness of management interventions in a hospital using SAS Text Miner |
Text Miner |
source |
7 |
| SESUG |
2012 |
The Keouk County CAFO Study: A Complementary Analysis Using Classification Trees in SAS Enterprise Miner |
Leonard Gordon |
source |
8 |
| SESUG |
2012 |
Where Should I Dig? What to Do Before Mining Your Data |
Stephanie R. Thompson |
source |
3 |
| MWSUG |
2012 |
An Analysis of Diabetes Risk Factors Using Data Mining Approach |
Akkarapol Sa-ngasoongsong,
Jongsawas Chongwatpol |
|
11 |
| MWSUG |
2012 |
Methods for Interaction Detection in Predictive Modeling Using SAS |
Douglas Thompson |
|
13 |
| MWSUG |
2012 |
SAS Grid: Grid Enablement of SAS |
Adam H. Diaz |
|
4 |
| MWSUG |
2012 |
SAS Grid: Grid Scheduling Policy and Resource Allocation |
Adam H. Diaz |
|
8 |
| MWSUG |
2012 |
Using Base SAS and SAS Enterprise Miner to Develop Customer Retention Modeling |
Rex Pruitt |
|
17 |
| WUSS |
2012 |
Building, refining & scoring financial transaction sequence analytics |
Robin E. Way |
source |
12 |
| WUSS |
2012 |
Moving Beyond Caveman Communication to Explain the Statistics Behind Your Model:So Easy a PhD Can Do It! |
Kari Kelso |
source |
9 |
| WUSS |
2012 |
SAS In-Database Procedures on eBay's Teradata System Reduces Processing Time by a Factor of 4 |
Arun Akkinapalli,
Mithun Yarlagadda,
Gurudev Karanth,
John Prenner |
source |
11 |
| WUSS |
2012 |
SAS Rule-Based Codebook Generation for Exploratory Data Analysis |
Ross Bettinger |
source |
8 |
| SGF |
2012 |
A New Age of Data Mining in the High-Performance World |
David R. Duling,
Wayne Thompson,
Jared Dean |
source |
11 |
| SGF |
2012 |
An Experimental Comparison of Classification Techniques for Imbalanced Credit Scoring Data Sets Using SAS Enterprise Miner |
Iain L. Brown |
source |
14 |
| SGF |
2012 |
Application of Time Series Clustering Using SAS Enterprise Miner for a Retail Chain |
Karthik Nakkeeran,
Satish Garla,
Goutam Chakraborty |
source |
9 |
| SGF |
2012 |
Better, Consistent Customer Experience from Analytically Based Real-Time Decisions |
Toshi Tsuboi |
source |
8 |
| SGF |
2012 |
Building WOE Binned LGD Scorecards using SAS Enterprise Miner |
Anthony J. van Berkel,
Naeem Siddiqi |
source |
14 |
| SGF |
2012 |
Classification of Customers Textual Responses via Application of Topic Mining |
Anil K. Pantangi,
Goutam Chakraborty |
source |
6 |
| SGF |
2012 |
Cluster Mapping of Medicare Severity Diagnosis-Related Groups for ICD-10 Conversions |
Keith A. Jones |
source |
11 |
| SGF |
2012 |
Comparison of K-Means, Normal Mixtures and Probabilistic-D Clustering for B2B Segmentation Using Customers Perceptions |
Satish Garla,
Gary Gaeth,
Goutam Chakraborty |
source |
8 |
| SGF |
2012 |
Constructing a Credit Risk Scorecard Using Predictive Clusters |
Andres F. Gonzalez,
Alejandro Correa Bahnsen,
Ana C. Nieto,
Darwin A. Amezquita |
source |
13 |
| SGF |
2012 |
CSI: Customer Segmentation Intelligence for Increasing Profits |
Darius S. Baer |
source |
13 |
| SGF |
2012 |
Developing a Predictive Model for Customer Trip Purpose to Be Integrated into Enterprise Strategy and Analytics |
Jonathan Levine |
source |
16 |
| SGF |
2012 |
Easily Add Significance Testing to your Market Basket Analysis in SAS Enterprise Miner |
Michael Faron,
Goutam Chakraborty |
source |
6 |
| SGF |
2012 |
Its About Time: Discrete Time Survival Analysis using SAS Enterprise Miner |
Sascha Schubert,
Susan Haller,
Taiyeong Lee |
source |
15 |
| SGF |
2012 |
Kass Adjustments in Decision Trees on Binary/Interval Target |
Manoj K. Immadi |
source |
9 |
| SGF |
2012 |
Net Lift Model for Effective Direct Marketing Campaigns at 1800flowers.com |
Roman Kubiak |
source |
5 |
| SGF |
2012 |
SAS In-Database Capability: Smart Architecture |
Gaurav K. Agrawal |
source |
10 |
| SGF |
2012 |
The Path to Developing Your Organization's SAS Skills |
Jonathan Boase,
Donald E. Kros |
source |
4 |
| SGF |
2012 |
Use of Cutoff and SAS Code Nodes in SAS Enterprise Miner to Determine Appropriate Probability Cutoff Point for Decision Making with Binary Target Models |
Yogen Shah |
source |
6 |
| SGF |
2012 |
Using SAS Enterprise BI and SAS Enterprise Miner to Reduce Student Attrition |
Matt T. Bogard,
Chris James,
Tuesdi Helbig,
Gina Huff |
source |
10 |
| SGF |
2012 |
Variable Selection for Multivariate Cointegrated Time Series Prediction with PROC VARCLUS in SAS Enterprise Miner 7.1 |
Akkarapol Sa-ngasoongsong,
Satish T. Bukkapatnam |
source |
12 |
| SCSUG |
2011 |
Kass Adjustments in Decision Trees on Binary/Interval Target Variable |
Manoj Immadi |
source |
10 |
| SCSUG |
2011 |
Understanding the Anatomy of a SAS Deployment: What's in My Server Soup? |
Mark L. Schneider |
source |
18 |
| SCSUG |
2011 |
Use of Cutoff and SAS Code node in SAS Enterprise Miner to determine appropriate probability cutoff point for decision making with binary target models |
Yogen Shah |
source |
7 |
| SESUG |
2011 |
Find Potential Fraud Leads Using Data Mining Techniques |
Find Potential Fraud Leads,
Qiling Shi,
Carrie McBrayer |
source |
6 |
| WUSS |
2011 |
Assessing resource adequacy uncertainty in California electricity summer demand using the MCMC procedure in SAS Enterprise MinerTM |
Miguel Garcia-Cerrutti |
source |
12 |
| WUSS |
2011 |
ChiD, A Chi-2 - Based Discretization Algorithm |
Ross Bettinger |
source |
9 |
| WUSS |
2011 |
Comparison of K-Means, Normal Mixtures and Probabilistic-D Clustering for B2B Segmentation Using Customers Perceptions |
Satish Garla |
source |
9 |
| WUSS |
2011 |
Understanding the Anatomy of a SAS Deployment: What's in My Server Soup? |
Connie Robison |
source |
18 |
| MWSUG |
2011 |
SAS Analytic Solutions Win in Response to the "CARD Act of 2009" |
Rex Pruitt |
|
9 |
| MWSUG |
2011 |
Using SAS to Find the Best K for K-Nearest-Neighbor Classification |
Charlie Huang |
|
14 |
| MWSUG |
2011 |
Using the SAS BI Platform to Support Decision-making at a University |
Ryan Cherland |
|
15 |
| NESUG |
2011 |
An Optimal Search Process of "Eigen Knots" for Spline Logistic Regression |
John Gao,
Cheryl Caswell |
|
7 |
| NESUG |
2011 |
Understanding the Anatomy of a SAS Deployment: What's in My Server Soup? |
Mark L. Schneider |
|
18 |
| PharmaSUG |
2011 |
Classification of frequent snoring from routine medical examinations using the NHANES Database |
Barry W. Row |
source |
11 |
| PharmaSUG |
2011 |
Clinical Trials Versus Health Outcomes Research: SAS/STAT Versus SAS Enterprise Miner |
Patricia B. Cerrito |
source |
15 |
| SGF |
2011 |
Best Practices for the SAS Scoring Accelerator for DB2 |
Matthias Nicola,
Kim Sherrill |
source |
10 |
| SGF |
2011 |
Bump Hunting With SAS: A Macro Approach to Employing PRIM |
Jennifer Sniadecki |
source |
9 |
| SGF |
2011 |
Comparison of Probabilistic-D and k-Means Clustering in Segment Profiles for B2B Markets |
Dipanjan K. Dey,
Satish Garla,
Goutam Chakraborty |
source |
9 |
| SGF |
2011 |
Creating a SAS Model Factory Using In-Database Analytics |
John Spooner |
source |
8 |
| SGF |
2011 |
Data Mining in SAS with Open-Source Software |
Zhengping Ma |
source |
11 |
| SGF |
2011 |
Data Mining Using JMP |
Murphy Choy |
source |
9 |
| SGF |
2011 |
Distance Mapping in Health and Health Care: SAS as a Tool for Health Geomatics |
Barbara B. Okerson |
source |
12 |
| SGF |
2011 |
Explicit SQL Pass-Through: Is It Still Useful? |
Frank Capobianco |
source |
5 |
| SGF |
2011 |
Genetic Algorithm Optimization for Selecting the Best Architecture of a Multi-Layer Perceptron Neural Network: A Credit Scoring Case |
Alejandro Correa,
Andres F. Gonzalez,
Camilo Ladino |
source |
8 |
| SGF |
2011 |
Impact of Regulations on Risk and Trading Analytics in Capital Markets |
Jeff Hong |
source |
13 |
| SGF |
2011 |
Implementing a Data Mining Solution with SAS and Teradata |
Angela Watson |
source |
3 |
| SGF |
2011 |
Patron Analytics in the Casino and Gaming Industry: How the House Always Wins |
Scott W. Sutton |
source |
7 |
| SGF |
2011 |
Ratemaking Using SAS Enterprise Miner: An Application Study |
Billie Anderson |
source |
20 |
| SGF |
2011 |
SAS Analytic Solutions Win in Response to the Credit CARD Act of 2009 |
Rex Pruitt |
source |
9 |
| SGF |
2011 |
Sentiment Mining Using SAS Text Miner |
Patricia B. Cerrito,
John C. Cerrito |
source |
17 |
| SGF |
2011 |
Taking Disease and Health Management Analytics into the Next Generation |
George S. Habek |
source |
13 |
| SGF |
2011 |
Teradata for the SAS Programmer: Ordered Analytical Functions, Hash Objects, ANSI SQL: 2003 |
Richard Andrews,
Jignesh Miyani |
source |
11 |
| SGF |
2011 |
The Anti-Curse: Creating an Extension to SAS Enterprise Miner Using PROC ARBORETUM |
Andrew S. Cathie |
source |
11 |
| SGF |
2011 |
Time Series Data Mining with SAS Enterprise Miner |
Sascha Schubert,
Taiyeong Lee |
source |
12 |
| SGF |
2011 |
Understanding Drivers of Achieving Academic Success in University Students |
David Dobson |
source |
17 |
| SGF |
2011 |
Understanding the Anatomy of a SAS Deployment: What's in My Server Soup? |
Mark L. Schneider,
Donna Bennett,
Connie Robison |
source |
17 |
| SGF |
2011 |
Using Real-Time Analytics to Manage Next Best Offer |
Christopher R. Toth |
source |
5 |
| SGF |
2011 |
Using SAS Enterprise Miner for Resort Profit Optimization: How to Systematically Provide Individual Consumers with Personalized Rates and Offers to Unleash Total Profit Optimization |
Marco Benvenuti |
source |
6 |
| NESUG |
2010 |
Take a Whirlwind Tour Around SAS 9.2 |
Diane Hatcher,
Robert Craige |
|
8 |
| NESUG |
2010 |
US Army Personnel Friction Analysis |
Jose A. Ramirez,
Mark Zais |
|
12 |
| WUSS |
2010 |
Getting Started with SAS OnDemand for Academics: Enterprise Miner |
Gerardo Perez-Lizarraga |
source |
9 |
| WUSS |
2010 |
Take a Whirlwind Tour Around SAS 9.2 |
Justin Choy |
source |
8 |
| PHUSE EU |
2010 |
Using Data and Text Mining to drive Innovation |
David Smith |
source
presentation source |
6 |
| MWSUG |
2010 |
Adequacy and Information Values: Two Tools for Ranking Predictors in Generalized Linear Models |
Douglas Thompson |
|
21 |
| MWSUG |
2010 |
Evaluation of Methods to Determine Optimal Cut Points for Predicting Mortgage Default |
Valentin Todorov,
Douglas Thompson |
|
11 |
| MWSUG |
2010 |
Gastrointestinal Diseases: Diagnoses, Misdiagnoses, and Comorbidities |
Pedro Ramos |
|
4 |
| MWSUG |
2010 |
Getting from SAS 9.1.3 to SAS 9.2: Practicalities of the Automated Tools |
Diane Hatcher |
|
10 |
| MWSUG |
2010 |
Medical Guidelines: Consensus Panel Versus Healthcare Analytics |
Patricia B. Cerrito |
|
17 |
| MWSUG |
2010 |
Take a Whirlwind Tour Around SAS 9.2 |
Diane Hatcher |
|
8 |
| MWSUG |
2010 |
The Applied Use of Population Stability Index (PSI) in SAS Enterprise Miner |
Rex Pruitt |
|
14 |
| MWSUG |
2010 |
Using Base SAS and SAS Enterprise Miner to Develop Customer Retention Modeling |
Rex Pruitt |
|
17 |
| SESUG |
2010 |
Detecting Medicaid Data Anomalies Using Data Mining Techniques |
Shenjun Zhu,
Qiling Shi,
Aran Canes |
source |
9 |
| SESUG |
2010 |
Distance Mapping in Health and Health Care: SAS as a Tool for Health Geomatics |
Barbara B. Okerson |
source |
12 |
| SESUG |
2010 |
Take a Whirlwind Tour Around SAS 9.2 |
Diane Hatcher |
source |
8 |
| SESUG |
2010 |
Your Friendly Neighborhood Webcrawler: A Guide to Crawling the Web with SAS |
Jake Bartlett,
Alicia Bieringer,
James A. Cox |
source |
6 |
| SGF |
2010 |
An Analytical Approach to Determining Customer Value in the Property and Casualty Insurance Industry |
Roosevelt Mosley |
source |
20 |
| SGF |
2010 |
Data and Text Mining in SAS Warranty Analysis 4.2 |
Ned Maran,
Wei Huang |
source |
13 |
| SGF |
2010 |
Improving Credit Risk Scorecards with Memory-Based Reasoning to Reject Inference with SAS Enterprise Miner Software |
Billie Anderson,
James A. Cox,
David R. Duling,
Susan Haller,
Naeem Siddiqi |
source |
13 |
| SGF |
2010 |
Improving the Defense Lines: The Future of Fraud Detection in the Insurance Industry (with Fraud Risk Models, Text Mining, and Social Networks) |
Terisa Roberts |
source |
7 |
| SGF |
2010 |
Investigating the Impact of Medicare Part D on Diabetes Medications Using SAS Enterprise Miner and Survival Analysis |
Xiao Wang |
source |
13 |
| SGF |
2010 |
Migration from SAS 9.1.3 to SAS 9.2: Practicalities of the Automated Tools |
Diane Hatcher |
source |
10 |
| SGF |
2010 |
More than Models: The Data Mining Team |
Stephanie R. Thompson |
source |
6 |
| SGF |
2010 |
Rapid Predictive Modeling for Customer Intelligence |
Wayne Thompson,
David R. Duling |
source |
12 |
| SGF |
2010 |
Segmenting Textual Data on Automobile Insurance Claims |
David Dobson |
source |
9 |
| SGF |
2010 |
Staying Highly Available Using SAS Grid Manager: The Performance Manager Application at Commerzbank AG |
Cheryl Doninger,
Jochen Kirsten |
source |
15 |
| SGF |
2010 |
The Applied Use of Population Stability Index in SAS Enterprise Miner |
Rex Pruitt |
source |
15 |
| SGF |
2010 |
The Power of the Group Processing Facility in SAS Enterprise Miner |
Sascha Schubert |
source |
13 |
| SGF |
2010 |
Using the SAS System and SAS Enterprise Miner for Data Mining: A Study of Cancer Survival at the Mayo Clinic |
Leonard Gordon |
source |
6 |
| SGF |
2010 |
Your Friendly Neighborhood Webcrawler: A Guide to Crawling the Web with SAS |
Jake Bartlett,
Alicia Bieringer,
James A. Cox |
source |
6 |
| SESUG |
2009 |
Customer Retention Predictive Modeling in HealthCare Insurance Industry |
Jin Su,
Kimberly Cooper,
Tina Robinson,
Brad Jordan |
source |
8 |
| SESUG |
2009 |
High Performance Analytics with In-Database Processing |
High Performance |
source |
8 |
| MWSUG |
2009 |
A Comparison of Decision Tree and Logistic Regression Model |
Xianzhe Chen |
|
10 |
| MWSUG |
2009 |
Demonstration of Organic Growth Modeling for B to B Marketing |
Karen Ziton |
|
15 |
| MWSUG |
2009 |
High Performance Analytics with In-Database Processing |
Stephen Brobst,
Keith Collins,
Paul Kent,
Michael Watzke |
|
8 |
| MWSUG |
2009 |
Irritable Bowel Syndrome and Mood Disorders |
Pedro Ramos |
|
6 |
| MWSUG |
2009 |
Outcome Research for Diabetic Inpatients with SAS Enterprise Miner 5.2 |
Xiao Wang |
|
21 |
| MWSUG |
2009 |
Predictive Modeling in Enterprise Miner Versus Regression |
Patricia B. Cerrito |
|
27 |
| MWSUG |
2009 |
Using Base SAS and SAS Enterprise Miner to Develop Customer Retention Modeling |
Rex Pruitt |
|
17 |
| PNWSUG |
2009 |
High Performance Analytics with In-Database Processing |
Stephen Brobst,
Keith Collins,
Paul Kent,
Mike Watzke |
|
8 |
| NESUG |
2009 |
Ad Hoc Data Preparation for Analysis Using SAS Enterprise Guide |
I-Kong B. Fu |
|
11 |
| NESUG |
2009 |
Deciding if the EM Algorithm is the Right Choice |
Michael B. Moldoff |
|
3 |
| NESUG |
2009 |
Process Excursion Detection using Statistical Analysis Methodologies in High Volume Semiconductor Production |
Peter Frankwicz |
|
8 |
| SGF |
2009 |
Ad Hoc Data Preparation for Analysis Using SAS Enterprise Guide |
I-Kong B. Fu,
Wayne Thompson,
Mike Porter |
source |
11 |
| SGF |
2009 |
ISO's Evolution to BI on the Grid: A Customer Perspective |
Phil Hatfield |
source |
6 |
| SGF |
2009 |
New Features in Optimization with SAS/OR |
Edward P. Hughes,
Trevor D. Kearney |
source |
19 |
| SGF |
2009 |
Optimizing Product Formulation with JMP and SAS Enterprise Miner |
John Leveille,
Wayne J. Levin |
source |
6 |
| SGF |
2009 |
Reject Inference Techniques Implemented in Credit Scoring for SAS Enterprise Miner |
Billie Anderson,
Susan Haller,
Naeem Siddiqi |
source |
11 |
| SGF |
2009 |
The Increased Utilization of Analytics and How Academic Programs Are Responding to Job Market Demands by Leveraging Predictive Modeling with SAS Enterprise Miner Certification |
Goutam Chakraborty,
Julie Petlick |
source |
4 |
| SGF |
2009 |
The Next Generation: SAS Enterprise Miner 6.1 |
David R. Duling,
Wayne Thompson |
source |
10 |
| SGF |
2009 |
The Path to Profitable Analytics: Via Predictive Analytics to Marketing Automation |
Petr Ptacnik |
source |
10 |
| SGF |
2009 |
The Problem of Regression Assumptions and the Use of Predictive Modeling |
Patricia B. Cerrito |
source |
20 |
| SGF |
2009 |
Using Base SAS and SAS Enterprise Miner to Develop Customer Retention Modeling Strategies |
Rex Pruitt |
source |
17 |
| SGF |
2009 |
Using SAS OnDemand for Academics to Meet Changing Student Needs, Reduce Software Access Barriers, and Grow SAS Skills |
Tom Edds,
Ron Statt |
source |
6 |
| SESUG |
2008 |
Introduction to the SAS 9 Business Intelligence Platform: A Tutorial |
Gregory S. Barnes Nelson |
source |
12 |
| SESUG |
2008 |
Lithium Battery Analysis: Probability of Failure Assessment Using Logistic Regression |
Travis A. Moebes |
source |
9 |
| SESUG |
2008 |
Tailoring the use of SAS Enterprise Miner |
Sascha Schubert |
source |
14 |
| SESUG |
2008 |
Teaching Data Mining: the University of Alabama and SAS |
Michael D. Conerly,
J. Michael Hardin |
source |
5 |
| PHUSE EU |
2008 |
CDISC Implementation Strategies: Exploit your data assets while still giving the FDA what they want |
David Smith |
source |
9 |
| MWSUG |
2008 |
Classification of Breast Cancer Cells Using JMP |
Marie Gaudard |
|
34 |
| MWSUG |
2008 |
The Difference Between Predictive Modeling and Regression |
Patricia B. Cerrito |
|
19 |
| NESUG |
2008 |
Effective Problem Solving in Teams |
Fabian Robinson |
|
6 |
| NESUG |
2008 |
From Play-Doh to Real Dough: Helping Students Develop Strong SAS Skills to Jump Start Their Careers in Analytics |
Elizabeth Ceranowski |
|
7 |
| NESUG |
2008 |
Proc Logistic Plus: The Power Of Variable Transformations |
Krishna Mehta,
Nitin K. Jain,
Varun Aggarwal |
|
4 |
| PharmaSUG |
2008 |
From Soup to Nuts: Practices in Data Management for Analytical Performance |
David R. Duling |
|
25 |
| PharmaSUG |
2008 |
SAS Certification: Are You Ready to Put Your SAS Skills to the Test? |
Dawn Hopper |
|
9 |
| PharmaSUG |
2008 |
Text Mining to Summarize Complicated Datasets Containing Structured, Nominal Data |
Hamed Zahedi |
|
10 |
| SGF |
2008 |
A SAS Text Mining Approach to Predicting the Resolvability of Disputes between eBays Sellers and Buyers |
Kevin S. Henning,
Zhangxi Lin |
source |
12 |
| SGF |
2008 |
Balancing the Load: SAS Server Technologies for Scalability |
Cheryl Doninger,
Jason Spruill |
source |
13 |
| SGF |
2008 |
Cool New Features in SAS Enterprise Miner 5.3 |
David R. Duling,
Sascha Schubert,
Wayne Thompson |
source |
12 |
| SGF |
2008 |
Data Integration with SAS Intelligence Storage: How a business Division in a Fortune 50 Company Uses SAS Scalable Performance Data Server to Make Better Decisions |
Stephen C. Scott,
Brian Herzog,
Justin Eisenzimmer |
source |
23 |
| SGF |
2008 |
From Soup to Nuts: Practices in Data Management for Analytical Performance |
David R. Duling,
Howard Plemmons Jr.,
Nancy A. Rausch |
source |
24 |
| SGF |
2008 |
How SAS 9 Allows the Delivery of the Power of Predictive Analytics and Forecasting to the Masses |
David Pope |
source |
10 |
| SGF |
2008 |
Identifying Potential Default Loan Applicants: A Case Study of Consumer Credit Decision for Chinese Commercial Bank |
Zhangxi Lin,
Qiwei Gan,
Binjie Luo |
source |
12 |
| SGF |
2008 |
In Search for a Golden Algorithm |
Tamara S. Slipchenko,
Candice Bowman,
Catherine Sugar,
Allen L. Gifford |
source |
9 |
| SGF |
2008 |
It's 9:00 AM: Do You Know Where Your Critical Talent Is? Retention Analytics for Human Capital Management |
Lynn Creecy,
Bradley W. Klenz |
source |
11 |
| SGF |
2008 |
Lithium Battery Analysis: Probability of Failure Assessment Using Logistic Regression |
Travis A. Moebes |
source |
9 |
| SGF |
2008 |
Making Sense of Multi-Core Processor Technology for the SAS Environment |
Carl E. Ralston |
source |
9 |
| SGF |
2008 |
SAS Certification: Are You Ready to Put Your SAS Skills to the Test? |
Dawn Hopper |
source |
9 |
| SGF |
2008 |
SAS Grid 101: How It Can Modernize Your Existing SAS Environment |
Cheryl Doninger,
Glenn Horton |
source |
13 |
| SGF |
2008 |
SAS/OR: Rigorous Constrained Optimized Binning for Credit Scoring |
Ivan Oliveira,
Susan Haller,
Manoj Chari |
source |
10 |
| SGF |
2008 |
Survival Data Mining: Treatment of Chronic Illness |
Patricia B. Cerrito,
John C. Cerrito |
source |
19 |
| SGF |
2008 |
Tailoring the use of SAS Enterprise Miner |
Sascha Schubert |
source |
14 |
| SGF |
2008 |
Text and Data Mining to Investigate Expenditures on Prescribed Medicines |
Guoxin Tang |
source |
7 |
| SGF |
2008 |
The Early Warning Project: Prewarning and Avoiding Problems and Costly Downtime in Complex Industrial Processes |
Torulf Mollestad,
Frode Oplenskedal |
source |
12 |
| SGF |
2008 |
Understanding Your Customer: Segmentation Techniques for Gaining Customer Insight and Predicting Risk in the Telecom Industry |
Glendon Cross,
Wayne Thompson |
source |
14 |
| SGF |
2008 |
Use of Text Mining to Predict Patient Compliance |
Christiana Petrou |
source |
15 |
| SGF |
2008 |
Using SAS Enterprise Miner to Prescribe a Pre-Screen Mailing |
Rex Pruitt |
source |
6 |
| SGF |
2008 |
Whats New in Optimization with SAS/OR |
Edward P. Hughes,
Trevor D. Kearney |
source |
16 |
| NESUG |
2007 |
&Degrees. of Separation: Social Network Analysis Using The SAS System |
Shane L. Hornibrook |
|
8 |
| NESUG |
2007 |
A SAS Constellation Diagram Has Many Faces |
Shi-Tao Yeh |
pdf |
17 |
| NESUG |
2007 |
Navigating the SAS Training Experience |
Amy Peters |
|
5 |
| NESUG |
2007 |
Variable Selection and Variable Transformations in SAS Enterprise Miner 5.2 |
Kattamuri S. Sarma |
|
12 |
| SESUG |
2007 |
Data Mining Episode Groupers |
Patricia B. Cerrito |
source |
13 |
| SESUG |
2007 |
Introduction to the SAS 9 Business Intelligence |
Gregory S. Barnes Nelson |
source |
12 |
| SESUG |
2007 |
Making Web Results Relevant with SAS |
Russell Albright,
Jake Bartlett,
David Bultman |
source |
12 |
| SESUG |
2007 |
Mining Medicaid Encounter Data: What, Why and How? |
Wei Jiang |
source |
7 |
| MWSUG |
2007 |
Analyzing Survey Data Using Decision Trees |
Morgan C. Wang |
|
25 |
| MWSUG |
2007 |
Best Practices for Managing Predictive Models in a Production Environment |
Robert Chu |
|
10 |
| MWSUG |
2007 |
Identifying and Overcoming Common Data Mining Mistakes |
Doug Wielenga |
|
20 |
| WUSS |
2007 |
Case Study: Development of an HIV casefinding algorithm with SAS Enterprise Miner |
Tamara Slipchenko,
Candice Bowman,
Yuexin (Cindy) Chen,
Catherine Sugar,
Allen L. Gifford |
source |
9 |
| WUSS |
2007 |
Data Mining Using SAS Enterprise Miner |
Randall Matignon |
source |
10 |
| WUSS |
2007 |
LDAP and Integrated Technologies: A Simple Primer |
Brian Kowalczyk,
Richard Kerwin |
source |
7 |
| WUSS |
2007 |
Utility Macros for Enterprise Miner |
Daniel P. Edstrom |
source |
5 |
| PHUSE EU |
2007 |
Data mining in the clinical research environment |
David Smith |
source |
7 |
| PHUSE EU |
2007 |
Introduction to the SAS9 Business Intelligence platform |
Gregory S. Barnes Nelson |
source |
12 |
| PharmaSUG |
2007 |
Clinical Adverse Events Data Analysis and Visualization |
Shi-Tao Yeh |
|
12 |
| PharmaSUG |
2007 |
Introduction to the SAS 9 Business Intelligence Platform: A Tutorial |
Gregory S. Barnes Nelson |
|
12 |
| SGF |
2007 |
Best Practices for Implementing a BI Strategy with SAS |
Mike Varney,
Brian Vanderlinden |
source |
10 |
| SGF |
2007 |
Best Practices for Managing Predictive Models in a Production Environment |
Robert Duling,
David M. Thompson,
Wayne Chu |
source |
10 |
| SGF |
2007 |
Critical Success Factors for Rate Making with SAS Enterprise Miner |
Hrushikesh Khopkar,
Jay King |
source |
17 |
| SGF |
2007 |
Data Mining Physician Decisions for MRSA |
Hamed Zahedi |
source |
8 |
| SGF |
2007 |
Data Mining to Investigate the Prescribing of Medications Longitudinally |
Mussie A. Tesfamicael |
source |
17 |
| SGF |
2007 |
Empowering Your SAS Business Intelligence End Users via a SAS Stored Process |
David Pope |
source |
8 |
| SGF |
2007 |
Identifying and Overcoming Common Data Mining Mistakes |
Doug Wielenga |
source |
20 |
| SGF |
2007 |
Introduction to SAS9 Business Intelligence-A Tutorial |
Gregory S. Barnes Nelson |
source |
12 |
| SGF |
2007 |
Making Web Results Relevant with SAS |
Russell D. Bartlett,
Jake Bultman,
David Albright |
source |
12 |
| SGF |
2007 |
Methodology for Railway Demand Forecasting Using Data Mining |
Giovanni M. Viglioni |
source |
11 |
| SGF |
2007 |
Mining Transaction/Order Data Using the SAS Enterprise Miner Association Node |
Xinli Bao |
source |
5 |
| SGF |
2007 |
Navigating the SAS Training Experience |
Amy Peters |
source |
5 |
| SGF |
2007 |
Optimization with SAS/OR--What It Is, What's New, and How It Adds Value |
Trevor Hughes,
Ed Kearney |
source |
12 |
| SGF |
2007 |
Predicting Software Maintenance Outcomes Using Data Mining and Text Mining |
Uzma Raja |
source |
9 |
| SGF |
2007 |
Predictive Modeling in Higher Education |
Tom Bohannon |
source |
14 |
| SGF |
2007 |
SAS Constellation Diagram Has Many Faces |
Shi-Tao Yeh |
source |
16 |
| SGF |
2007 |
SAS Response: Revenue Assurance for Energy ... Using SAS Solutions to Leverage Corporate Intelligence to Fuel Effective, Forward-Looking Decisions in Volatile Markets |
Craig McMane,
Steve Carothers |
source |
11 |
| SGF |
2007 |
Ubiquitous Scoring of 1000+ Warranty Categories Using Predictive Rules Derived from Text |
Barry deVille |
source |
8 |
| SCSUG |
2006 |
Data Mining at the Texas State Auditor's Office |
Thomas J. Winn Jr. |
|
11 |
| SCSUG |
2006 |
What's New in SAS Enterprise Miner 5.2 |
Wayne Thompson,
David R. Duling |
|
10 |
| SESUG |
2006 |
Comparing Time series, Generalized Linear Models and Artificial Neural Network Models for Transactional Data Analysis |
Joseph Twagilimana |
source |
9 |
| SESUG |
2006 |
Gene Expression Profiling of DNA Microarray Data using Association rule and Structural Equation Modeling |
Mussie A. Tesfamicael |
source |
7 |
| SESUG |
2006 |
Predictive Modeling to Analyze Hospital Charges Versus Reimbursements |
Chakib Battioui |
source |
12 |
| SESUG |
2006 |
Using SAS Enterprise Miner to Examine General Education Issues |
Patricia B. Cerrito |
source |
12 |
| WUSS |
2006 |
Find the Best Prospects for a New Product by Using a Data Mining Model |
Ting Wu |
source |
8 |
| WUSS |
2006 |
Text Mining Internet Discussion Groups: an Automotive Case Study |
John Wallace |
source |
7 |
| NESUG |
2006 |
&Degrees. of Separation: Social Network Analysis Using The SAS System |
Shane L. Hornibrook |
|
8 |
| NESUG |
2006 |
Linking SAS Analytics, U.S. Census Gazetteer Data and ArcView Geocoding Software for Medicare Fraud Screening |
Laurie Hamilton |
|
10 |
| NESUG |
2006 |
Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 |
Jodi Blomberg,
Jacqueline K. Long |
|
12 |
| PharmaSUG |
2006 |
Data Mining Methods to Link Multiple Drug Purchases and To Investigate Drug Costs to Consumers |
Patricia B. Cerrito |
|
15 |
| PharmaSUG |
2006 |
Socio-economic factors to utilization of the emergency department |
David Nfodjo |
|
4 |
| PharmaSUG |
2006 |
Using SAS ETL Studio to Convert Clinical Trials Data to the CDISC SDTM |
Barry R. Cohen |
|
10 |
| SUGI |
2006 |
A Comparison of the MIXED Procedure and the GLIMMIX Procedure |
Jennifer L. Ferrell |
source |
8 |
| SUGI |
2006 |
Banking on the Future - A Metadata Server Survival Guide |
Peter W. Eberhardt,
Andrew Farrer,
Zulfiqar Habib |
source |
11 |
| SUGI |
2006 |
Comparison of Data Preparation Methods for Use in Model Development with SAS Enterprise Miner |
Charles Manahan |
source |
10 |
| SUGI |
2006 |
Data and Text Mining the Electronic Medical Record to Improve Care and to Lower Costs |
Patricia B. Cerrito,
John C. Cerrito |
source |
20 |
| SUGI |
2006 |
Data Mining Techniques to Analyze a Library Database |
Chakib Battioui |
source |
9 |
| SUGI |
2006 |
Efficient Construction of a "One-Row-per-Subject" Data Mart for Data Mining |
Gerhard Svolba |
source |
16 |
| SUGI |
2006 |
Fraud Detection - A Primer for SAS Programmers |
Thomas J. Winn Jr. |
source |
6 |
| SUGI |
2006 |
Interactive Graphs from the SAS System |
Shi-Tao Yeh |
source |
10 |
| SUGI |
2006 |
Investigating Open Source Project Success - A Data Mining Approach to Model Formulation, Testing and Validation |
Uzma Raja,
Marietta J. Tretter |
source |
7 |
| SUGI |
2006 |
Offer Assignment with SAS Marketing Optimization |
Manoj Chari |
source |
18 |
| SUGI |
2006 |
Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 |
Jodi Blomberg,
Jacqueline K. Long |
source |
12 |
| SUGI |
2006 |
SAS Goes Grid - Managing the Workload across Your Enterprise |
Cheryl Doninger |
source |
15 |
| SUGI |
2006 |
Stay in Control of Your SAS Environment |
Vijayanand Rajandram |
source |
8 |
| SUGI |
2006 |
Text Mining with "Holographic" Decision Tree Ensembles |
Barry deVille |
source |
7 |
| SUGI |
2006 |
The Value of Real-Time Scoring Technology Using SAS |
Young Chun Kim |
source |
6 |
| SUGI |
2006 |
What's New in SAS Enterprise Miner 5.2 |
Wayne Thompson,
David R. Duling |
source |
10 |
| SESUG |
2005 |
Clustering Analysis of Micro Array Data |
John Schwarz |
source |
12 |
| SESUG |
2005 |
Data Mining Methods to Examine Thousands of Possibilities in Categorical Data |
Patricia B. Cerrito |
source |
13 |
| PHUSE EU |
2005 |
What SAS is doing for the FDA's Critical Path Initiative? |
Andrew T. Fagan |
source |
20 |
| MWSUG |
2005 |
A Comparison Of Linear Mixed Models To Generalized Linear Mixed Models: A Look At The Benefits Of Physical Rehabilitation In Cardiopulmonary Patients |
Jennifer Ferrell |
|
7 |
| MWSUG |
2005 |
An Overview Of The Data Mining Program At The University Of Central Florida |
Morgan C. Wang |
|
25 |
| MWSUG |
2005 |
Comparison Of Enterprise Miner And SAS/STAT For Data Mining |
Patricia B. Cerrito |
|
12 |
| MWSUG |
2005 |
Information Discovery Using Decision Trees |
Morgan C. Wang |
|
79 |
| MWSUG |
2005 |
Mining Transactional And Time Series Data |
Michael J. Leonard |
|
26 |
| MWSUG |
2005 |
Using SAS For Spatial Analysis |
Christina Pertrou |
|
5 |
| SUGI |
2005 |
A Proportional Hazards Approach to Campaign List Selection |
Charles Manahan |
source |
7 |
| SUGI |
2005 |
Automating Predictive Analysis to Predict Medicare Fraud |
Christine L. Warner |
source |
9 |
| SUGI |
2005 |
Combining Decision Trees with Regression in Predictive Modeling with SAS Enterprise Miner |
Kattamuri S. Sarma |
source |
10 |
| SUGI |
2005 |
Combining SAS Text Miner with the Association Node in SAS Enterprise Miner to Investigate Inventory Data |
Patricia B. Cerrito |
source |
10 |
| SUGI |
2005 |
Comparing the SAS Forecasting System with PROC HPF and SAS Enterprise Miner |
Patricia B. Cerrito |
source |
9 |
| SUGI |
2005 |
Decision Tree Validation: A Comprehensive Approach |
Sylvain Tremblay |
source |
8 |
| SUGI |
2005 |
Message Queue-Based Scoring Interface |
David R. Duling,
Robert Chu |
source |
14 |
| SUGI |
2005 |
Mining Transactional And Time Series Data |
Michael J. Leonard,
Brenda Wolfe |
source |
26 |
| SUGI |
2005 |
On GSForward-The Experimental Variable Selection Node in SAS Enterprise Miner 5.1 |
Leonardo Auslender |
source |
6 |
| SUGI |
2005 |
Predicting Workers' Compensation Insurance Fraud Using SAS Enterprise Miner 5.1 and SAS Text Miner |
Terry J. Woodfield |
source |
6 |
| SUGI |
2005 |
Structured Neural Network Techniques for Modeling Loyalty and Profitability |
Carl Lee,
Tim Rey,
James W. Mentele,
Michael Garver |
source |
13 |
| SUGI |
2005 |
Teaching Data Mining in a University Environment |
David A. Dickey |
source |
11 |
| SUGI |
2005 |
The Configuration Wizard: The Essential Final Step in Completing Your SAS BI Installation and Deployment |
Alec S. Fernandez |
source |
11 |
| SUGI |
2005 |
The University of Alabama and SAS Data Mining Certificate Partnership |
J. Michael Hardin,
Michael D. Conerly |
source |
4 |
| NESUG |
2004 |
Programming Techniques for Data Mining with SAS |
Samuel Berestizhevsky,
Tanya Kolosova |
|
14 |
| NESUG |
2004 |
Using SAS at SAS: The Mining of SAS Technical Support |
Annette M. Sanders,
Craig DeVault |
|
22 |
| SCSUG |
2004 |
Data Mining and the Use of SAS to Deploy Scoring Rules |
Neil S. Fleming |
|
13 |
| SCSUG |
2004 |
Fraud Detection - A Primer for SAS Programmers |
Thomas J. Winn Jr. |
|
9 |
| SESUG |
2004 |
Spatial Statistics Using the SAS Bridge for ESRI |
Patricia B. Cerrito,
Carol Hanchette,
William Dakan,
George R. Barnes,
Robert Forbes |
source |
15 |
| SESUG |
2004 |
Using SAS at SAS: The Mining of SAS Technical Support |
Annette M. Sanders,
Craig DeVault |
source |
22 |
| SESUG |
2004 |
Using SAS to Make an Independent Assessment of Electronic Medical Records |
Patricia B. Cerrito |
source |
17 |
| WUSS |
2004 |
Data Mining Using Neural Network Approaches Using SAS and Java |
David Bell |
source |
6 |
| MWSUG |
2004 |
Using SAS at SAS: The timing of SAS Tech Support |
Annette M. Sanders,
Craig DeVault |
|
22 |
| PharmaSUG |
2004 |
Critical Success Factors in Pharmaceutical Innovation |
Thomas H. Burger,
Michael S. Lajiness |
|
4 |
| PharmaSUG |
2004 |
Customizing Clinical Data Warehouse for Business Intelligence An analyst's view |
Haibin Shu Barr |
|
8 |
| PharmaSUG |
2004 |
The Analysis of Gene Markers and the Use of SAS Procedures to Examine MicroArray Data |
Patricia B. Cerrito |
|
14 |
| SUGI |
2004 |
9.1 Steps to Success with SAS 9.1 on Solaris 9 |
Maureen E. Chew |
source |
14 |
| SUGI |
2004 |
Balancing Data Quality Against Time and Money Constraints |
Susan B. Long,
Linda Roberge,
Jeff Lamicela,
Mummoorthy Murugesan |
source |
18 |
| SUGI |
2004 |
From Buzzwords to Business Value |
Liz Roche |
source |
19 |
| SUGI |
2004 |
SAS Intelligence Storage |
Jim Metcalf |
source |
2 |
| SUGI |
2004 |
Solutions to the Investigation of Healthcare Outcomes in Relationship to Healthcare Practice |
Patricia B. Cerrito |
source |
18 |
| SUGI |
2004 |
Text Mining Warranty and Call Center Data: Early Warning for Product Quality Awareness |
John Wallace,
Tracy A. Cermack |
source |
8 |
| SUGI |
2004 |
Understanding Customers through Data: A Data Miner's View |
Gordon Linoff |
source |
2 |
| SUGI |
2004 |
Using SAS at SAS: The Mining of SAS Technical Support |
Annette M. Sanders,
Craig DeVault |
source |
23 |
| WUSS |
2003 |
Principal Component Analysis, A Powerful Scoring Technique |
George C. J. Fernandez |
source |
6 |
| WUSS |
2003 |
Supporting Medical Research Analysis Using Effective Data Mining Tools: Creating a Well Documented SAS Analytical File from Multiple Warehoused ASCII Files |
Jay Gravink |
source |
3 |
| SEUGI |
2003 |
An Introduction to Genomics and SAS Scientific Discovery Solutions [presentation] |
Karen Miller |
source |
34 |
| SEUGI |
2003 |
China Railway Transporation Intelligent Decision Support System [presentation] |
Sun Yuanyun |
source |
24 |
| SEUGI |
2003 |
Controlling - tool of the financial management [presentation] |
Eva Micovska |
source |
38 |
| SEUGI |
2003 |
Customer Insight development in Vodafone Italy [presentation] |
Emanuele Baruffa |
source |
23 |
| SEUGI |
2003 |
Customer Lifetime Value and it's determination using the SAS Enterprise Miner and the SAS OROS-Software [presentation] |
Monika Seyerle |
source |
37 |
| SEUGI |
2003 |
Data Mining for Predicting Customer Satisfaction [presentation] |
Francesco Vivarelli |
source |
35 |
| SEUGI |
2003 |
Data Modelling in SAS - How SAS is Used for Research and Teaching to Enable Students to Become More Marketable [presentation] |
Iveta Stankovicova |
source |
30 |
| SEUGI |
2003 |
Getting to know retail customers [presentation] |
Megan Fitzsimmons |
source |
18 |
| SEUGI |
2003 |
How SAS Academic Intitative enables you to Bridge the gap between Academia and Business [presentation] |
Nina Hanke |
source |
35 |
| SEUGI |
2003 |
Integrated Analytics [presentation] |
Mark Ramsey |
source |
21 |
| SEUGI |
2003 |
Intelligence and Analytics - The Winning Combination [presentation] |
Betty Silver |
source |
36 |
| SEUGI |
2003 |
Intelligent Storage [presentation] |
Ingo Brenckmann |
source |
19 |
| SEUGI |
2003 |
Modelling the impact of climate change and weather related events [presentation] |
Seong Who Choo |
source |
31 |
| SEUGI |
2003 |
New Directions in SAS Enterprise Miner for SAS 9.1 [presentation] |
David R. Duling,
Sascha Schubert |
source |
26 |
| SEUGI |
2003 |
Optimizing Fraud Management Systems [presentation] |
Henrik Wagner,
Pushkar Bhat |
source |
29 |
| SEUGI |
2003 |
Pre-canned analytics and SAS Industry Intelligence Solutions [presentation] |
David Hartley,
Henrik Wagner |
source |
21 |
| SEUGI |
2003 |
Predicting churn behaviour for Optimus [presentation] |
Ricardo Almedia |
source |
20 |
| SEUGI |
2003 |
Risk Management @ Electrabel: exploiting SAP BW data for pricing and exposure reporting in Energy Trading [presentation] |
Brynseels |
source |
23 |
| SEUGI |
2003 |
SAS - Analytical CRM for Electricity Utilities [presentation] |
Ales Rojik |
source |
28 |
| SEUGI |
2003 |
SAS Supply Chain Intelligence - Or how to manage the Flood [presentation] |
Gerhard Held |
source |
37 |
| SEUGI |
2003 |
Second-generation data warehouse - strategic and tactics at the Vilnius Bank [presentation] |
Laukai |
source |
22 |
| SEUGI |
2003 |
Text Mining for tourism - The world of typical high quality restaurants in Piedmont [presentation] |
Roberto Fontana |
source |
78 |
| SEUGI |
2003 |
The Data Warehouse Methodology as an input for Data Mining Analysis in Public Health Service [presentation] |
Nathalie Coue |
source |
51 |
| SEUGI |
2003 |
The SAS Academic Intiative Featuring the Student Ambassadors: Building the future for our SAS Customers [presentation] |
Nina Hanke |
source |
42 |
| SEUGI |
2003 |
The SAS XML/A Web Services Framework [presentation] |
Anton Fuchs |
source |
41 |
| SEUGI |
2003 |
The Value of Text Mining in Pharmaceutical Laboratories [presentation] |
Elisabeth Maurice |
source |
29 |
| SEUGI |
2003 |
Using ASP.NET to leverage data and processes in SAS Servers [presentation] |
Anton Fuchs |
source |
33 |
| SEUGI |
2003 |
Using SAS Text Miner to extract intelligence from unstructured text sources [presentation] |
Bernd Drewes,
Manya Mayes |
source |
29 |
| SEUGI |
2003 |
Welcome to "Adminstration and Metadata" stream [presentation] |
Achim Granzen |
source |
36 |
| VIEWS |
2003 |
Customer churn - An operational comparison of logistic regression, decision tree & neural network models. |
Arun Parekkat |
|
4 |
| SUGI |
2003 |
Multistage Cross-Sell Model of Employers in the Financial Industry |
Kwan Park,
Steve Donohue |
source |
5 |
| SUGI |
2003 |
Shopping for Voters: Using Association Rules to Discover Relationships in Election Survey Data |
Mary F. MacDougall |
source |
5 |
| SUGI |
2003 |
STEPWISE Methods in Using SAS PROC LOGISTIC and SAS Enterprise MinerTM for Prediction |
Ernest S. Shtatland,
Ken Kleinman,
Emily M. Cain |
source |
6 |
| SUGI |
2003 |
The Use of Geographic Information Systems to Investigate Environmental Pollutants in Relationship to Medical Treatment |
Patricia B. Cerrito,
Robert Forbes,
George R. Barnes |
source |
6 |
| SUGI |
2003 |
Transactional Records Access Clearinghouse: SAS Based Warehouse and Mining Tools Keeps Tabs on U.S. Government |
Susan B. Long,
Linda Roberge,
Jeffrey T. Lamicela |
source |
6 |
| SUGI |
2003 |
Using Information Effectively to Make More Profitable Decisions: The Ten Letter Solution for Finance |
Frederick D. Busche,
Tom Everly,
Kirk Boothe |
source |
|
| SCSUG |
2002 |
Statistical Pattere Recognition Using Enterprise Miner and Self-Organizing Maps |
Keith A. Jones |
|
8 |
| SESUG |
2002 |
The Value of SAS in Manufacturing |
Eric C. Brinsfield |
source |
4 |
| SESUG |
2002 |
Using Decision Trees to Identify Medicare Part B Providers for Audit |
Noel McKetty |
source |
4 |
| SEUGI |
2002 |
18 months to make an Analytical CRM dream come true: results obtained by Vodafone Omnitel in B2B Churn Prevention [presentation] |
Alessandro Bernorio,
Paola Bauce |
source |
36 |
| SEUGI |
2002 |
An Introduction to Intelligent Warehousing [presentation] |
Paul Padley |
source |
13 |
| SEUGI |
2002 |
Bankruptcy scoring using the SAS Enterprise Miner [presentation] |
Michael Wetzel |
source |
18 |
| SEUGI |
2002 |
Buidling Credit Scorecards using SAS Enterprise Miner [presentation] |
John Lawrence,
Martin Crossley |
source |
11 |
| SEUGI |
2002 |
Building Strategic Advantage from a Single Customer View in Banking [presentation] |
Iain Jennings |
source |
15 |
| SEUGI |
2002 |
Custom Bankruptcy Scoring for Account Management [presentation] |
Edward Penner |
source |
10 |
| SEUGI |
2002 |
Customer Intelligence:The cornerstone of an Intelligent Strategy [presentation] |
Shaun Doyle |
source |
24 |
| SEUGI |
2002 |
Customer management from a data warehouse - A Journey not a Destination [presentation] |
Tal Shlasky |
source |
33 |
| SEUGI |
2002 |
Data Management and Data Analysis Solutions in Manufacturing: 10 Years Experience at Altis Semiconductor [presentation] |
J. L. Grolier |
source |
36 |
| SEUGI |
2002 |
Data Mining experiences in predicting TLC Churn [presentation] |
Marco Richeldi |
source |
20 |
| SEUGI |
2002 |
Data Mining In A Zero Latency Enterprise Environment [presentation] |
Luca Selvatici |
source |
24 |
| SEUGI |
2002 |
Datamining for Lifetime Value [presentation] |
Nigel Wigram |
source |
40 |
| SEUGI |
2002 |
Exploring Electoral Data with Enterprise Miner Using Self-Organizing Maps and Measures of Spatial Autocorrelation [presentation] |
Anabela Martins,
Fernando Lucas Bacao,
Sandra Catarino |
source |
12 |
| SEUGI |
2002 |
Forewarned is Forearmed: previenting defections of our best customers [presentation] |
Filippo Avigo,
Salvina Piccarreta |
source |
27 |
| SEUGI |
2002 |
How to maximize the effectiveness of 2000 salesmen [presentation] |
Antonello Mana,
Elena Delapiano,
Giorgio Rivero |
source |
24 |
| SEUGI |
2002 |
How to move from OPINIONS to FACTS [presentation] |
G. Ricci,
G. Zanini,
M. Rinchi |
source |
25 |
| SEUGI |
2002 |
Increasing Retail Banking Profitability through CRM: the UniCredito Italiano Case History [presentation] |
Giorgio Redenmagni |
source |
34 |
| SEUGI |
2002 |
Introduction to SAS Risk Management [presentation] |
Mika Hakuni |
source |
24 |
| SEUGI |
2002 |
Japanese Corporate Bankruptcy Prediction Model [presentation] |
Iwabuchi |
source |
22 |
| SEUGI |
2002 |
Know whom your cusomers listen to - Scoring for marketing channels reception propensity [presentation] |
Pawel Gasiorowski,
Wojciech Latusek |
source |
20 |
| SEUGI |
2002 |
Leveraging SAP BW with SAS for creating business value at Electrabel [presentation] |
Patrick Xhonneux,
Paul Bruynseels |
source |
22 |
| SEUGI |
2002 |
Mazimizing Campaign Return through Marketing Intelligence [presentation] |
Markus Matzak |
source |
16 |
| SEUGI |
2002 |
Medicaid Data Warehouse [presentation] |
Anthony Simmons |
source |
12 |
| SEUGI |
2002 |
New tools for a new context: Enterprise Miner in the French gas industry [presentation] |
Herve Augendre |
source |
17 |
| SEUGI |
2002 |
Outcome on a bank sales campaign based on scoring list [presentation] |
Gianluca Bo |
source |
20 |
| SEUGI |
2002 |
Payment Behavior Analysis and Prediction Project at a Telco Company [presentation] |
Osge Neslihan Cayci |
source |
21 |
| SEUGI |
2002 |
Predictin Customer Default Times using Survival Analysis Methods in SAS [presentation] |
Bart Baesens |
source |
16 |
| SEUGI |
2002 |
SAS Enterpise Miner: What does the future hold? [presentation] |
David R. Duling,
Sascha Schubert |
source |
45 |
| SEUGI |
2002 |
SAS Environment-Based Data Analysis [presentation] |
Marin |
source |
27 |
| SEUGI |
2002 |
Solving the complex problem of Energy Trading Risk Management [presentation] |
Allan Watson |
source |
35 |
| SEUGI |
2002 |
Terabyte-class data analysis for CRM in service provider [presentation] |
Ryo Mukae |
source |
18 |
| SEUGI |
2002 |
The corporate strategy and the CRM [presentation] |
Jose Luis Mena Cea |
source |
12 |
| SEUGI |
2002 |
The Norwich Union CRM Evolution |
Nunney |
source |
2 |
| SUGI |
2002 |
Communicating the Results of Predictive Models to Non-technical Audiences |
Andrew H. Karp |
source |
4 |
| SUGI |
2002 |
Data Warehousing in the Modern World: A Case Study Revisited |
Mary K. Tucker |
source |
8 |
| SUGI |
2002 |
Discriminant Analysis, A Powerful Classification Technique in Data Mining |
George C. J. Fernandez |
source |
9 |
| SUGI |
2002 |
IDW - The Next Generation Data Warehouse |
Larry D. Bramblett |
source |
5 |
| SUGI |
2002 |
The Knowledge Warehouse: The Next Step Beyond the Data Warehouse |
Anthony M. Dymond |
source |
8 |
| SUGI |
2002 |
To Neural or Not to Neural? - This Is the Question |
Leon L. Fedenczuk |
source |
6 |
| SUGI |
2002 |
Tree-based Models: Identification of Influential Factors under Condition of Instability |
Pavel Brusilovskiy,
Yillian Yuan |
source |
6 |
| SUGI |
2002 |
Using SAS Enterprise Miner for Data Quality Monitoring in the Veterans Health Administration's External Peer Review Program |
James H. Forsythe |
source |
5 |
| MWSUG |
2001 |
Modeling Lifetime Value in the Insurance Industry |
C. Olivia Parr Rud |
|
9 |
| NESUG |
2001 |
Introduction to Enterprise Miner. |
Destiny Corporation (a company) |
|
2 |
| VIEWS |
2001 |
Closing the Loop - Using SAS to Drive CRM |
Anton Hirschowitz |
|
13 |
| VIEWS |
2001 |
Data Mining and Statistical Models in Marketing Campaigns of BT Retail |
Francesco Vivarelli,
Martyn Johnson |
|
9 |
| VIEWS |
2001 |
Knowledge Discovery and Data Mining Applied to Engineering Applications [presentation] |
Shirley Williams |
|
22 |
| VIEWS |
2001 |
Methods Of Building an Enterprise Layer to Help Data Exploitation and Delivery |
Andrew Wilcox |
|
23 |
| VIEWS |
2001 |
SAS MSc Business Intelligence: A Flexible Approach |
Christine Straker,
Tony Tricker |
|
12 |
| VIEWS |
2001 |
The Use of Enterprise Miner with Large Volumes of Data, for Forecasting in an Automated Batch Process [presentation] |
Matthew Glasson,
Justine Eastman |
|
17 |
| VIEWS |
2001 |
Visualisation in SAS [presentation] |
Ian Sedgwick |
|
28 |
| WUSS |
2001 |
Intelligent Agents and Applications in Enterprise Computing |
Anthony M. Dymond |
source |
7 |
| WUSS |
2001 |
Using SAS Enterprise Miner for Forecasting Response and Risk |
Kattamuri S. Sarma |
source |
10 |
| WUSS |
2001 |
Using SAS for Mining Indirect Associations in Data |
Pang-Ning Tan,
Vipin Kumar,
Harumi Kuno |
source |
5 |
| SESUG |
2001 |
Web-Intelligence: A Primer |
Donald J. Henderson,
Ralph Mittl |
source |
10 |
| SCSUG |
2001 |
Web-Intelligence: A Primer |
Donald J. Henderson,
Ralph Mittl |
|
10 |
| SEUGI |
2001 |
A FMCG Company embracing the new challenges of CRM and Marketing Automation [presentation] |
Kerstin Plehwe |
source |
22 |
| SEUGI |
2001 |
A New Decision-Making Support Analysis for the Auditing Area at Banca Monte Dei Paschi Di Siena [presentation] |
Francesco Marzocchi,
Renato Coppi,
Roberto Tognazzi |
source |
28 |
| SEUGI |
2001 |
A retrospective evaluation of a data mining approach to fetal asphyxia at delivery in a hospital database [presentation] |
Olavi Kauhanen,
Seppo Heinonen |
source |
53 |
| SEUGI |
2001 |
Being the biggest - Becoming the best [presentation] |
Michał Michalak |
source |
20 |
| SEUGI |
2001 |
Beyond the Chip - Building Solutions for the Customer [presentation] |
Giovanni Chiabrando |
source |
21 |
| SEUGI |
2001 |
Building a compelling case for Enterprise Miner Within The Bank of Scotland [presentation] |
Simon Hughes |
source |
33 |
| SEUGI |
2001 |
Closing the Loop - Using SAS to drive CRM Integration [presentation] |
Anton Hirschowitz |
source |
32 |
| SEUGI |
2001 |
Customer Segmentation and retail product assortment [presentation] |
Barry Young |
source |
18 |
| SEUGI |
2001 |
Data Mining as Method to Streamline the Drug Discovery Process [presentation] |
Markus Duerring |
source |
20 |
| SEUGI |
2001 |
Data Mining at CDG Bank: an advantage or a requirement? [presentation] |
Elisabete Silva,
Henrique Nicola |
source |
25 |
| SEUGI |
2001 |
Data Mining In a Zero Latency Enterprise [presentation] |
Philip Bosinoff |
source |
36 |
| SEUGI |
2001 |
Data Warehouse Technology As The Main Building Block of the Modern IT Strategy of the Polish Customs Adminstration [presentation] |
Andrzej Tyrowicz |
source |
34 |
| SEUGI |
2001 |
e-Intelligence and e-CRM in a competitive new economy [presentation] |
Dorte Ransby |
source |
27 |
| SEUGI |
2001 |
Empowering the purchasing professional: The SAS solution for Supplier Relationship Management [presentation] |
Brigitte Ley |
source |
17 |
| SEUGI |
2001 |
Exploiting and extending the Multi Vendor Architecture [presentation] |
Achim Granzen |
source |
52 |
| SEUGI |
2001 |
Fast integration of Enterprise Guide and Enterprise Miner with WebHound [presentation] |
Klaus-Peter Huber,
Rainer Urbahns |
source |
12 |
| SEUGI |
2001 |
Fraud Detection in Healthcare - MBF's successful approach through SAS South Pacific Data Mining Discovery Centre [presentation] |
Jolie Reichel |
source |
14 |
| SEUGI |
2001 |
How to approach a segmentation project for ten million customers with SAS Enterprise Miner [presentation] |
Luis Miguel Muruzabal |
source |
26 |
| SEUGI |
2001 |
How To Find Your Way Around A Customer Database [presentation] |
Alberto Saccardi,
Fabio Marchetti |
source |
24 |
| SEUGI |
2001 |
Integration of campaign management and data mining at MTN South Africa [presentation] |
Marcelle Georgiev,
Mohan Namboodiri |
source |
22 |
| SEUGI |
2001 |
International Mail Order Business [presentation] |
Wil Amian |
source |
22 |
| SEUGI |
2001 |
Knowledge Solution for Credit Scoring [presentation] |
Henrik Wagner |
source |
26 |
| SEUGI |
2001 |
Minng-Driven Marketing - Penetrating Telco-Markets Successfully [presentation] |
Gunter Witsch,
Markus Ehl |
source |
19 |
| SEUGI |
2001 |
New Features and Future Directions for Enterprise Miner [presentation] |
David R. Duling,
Gerhard Held |
source |
31 |
| SEUGI |
2001 |
Preventing surrender by holders of life insurance policies [presentation] |
Gerhard Braas |
source |
20 |
| SEUGI |
2001 |
SAS & IUT of Vannes: 15 years of Partnership for Higher Competences in the Business Intelligence Economy [presentation] |
Ariane Liger-Belair Sioufi,
Jean Le Nouvel |
source |
21 |
| SEUGI |
2001 |
SAS 8e Release 2: An Overview [presentation] |
Achim Granzen |
source |
29 |
| SEUGI |
2001 |
SAS and CFMS Integration - Attacking Fraud in Next Generation Networks [presentation] |
Augusto Argento |
source |
35 |
| SEUGI |
2001 |
SAS Data Warehouse in the MKB [presentation] |
Szekeres Csaba |
source |
15 |
| SEUGI |
2001 |
SAS Process Intelligence: Closing the "Knowing-Doing" Gap to Deliver Value Through Process Efficiency, Effectiveness and Adaptability [presentation] |
Ian D. Cox |
source |
38 |
| SEUGI |
2001 |
Send in the Clones [presentation] |
Philip Whittall |
source |
22 |
| SEUGI |
2001 |
Silcon.com - The who, what, when, where and why of e-business [presentation] |
Tom Bureau |
source |
27 |
| SEUGI |
2001 |
Testing for the geographic representativeness of data subsets - The Nugget Effect or Degress of Difficulty [presentation] |
Frederick D. Busche |
source |
21 |
| SEUGI |
2001 |
The Automated Scoring Application Project [presentation] |
Carl A. Touchie |
source |
22 |
| SEUGI |
2001 |
The data mining process and SAS Enterprise Miner in Elisa Communications Corporation [presentation] |
Jaana Jarvelainen |
source |
20 |
| SEUGI |
2001 |
The SAS Solution for Enterprise Marketing Automation - Opening Session Demo [presentation] |
Nelle Schantz,
T. Randall Betancourt |
source |
43 |
| SEUGI |
2001 |
The SAS Text Mining Solution [presentation] |
Bernd Drewes,
Wayne Thompson |
source |
22 |
| SEUGI |
2001 |
The Use of Enterprise Miner with Large Volumes of Data, for Forecasting in an Automated Batch Process [presentation] |
Justine Eastman |
source |
12 |
| SEUGI |
2001 |
Using SAS Enterpise Miner Analytical CRM in Finance [presentation] |
Sascha Schubert |
source |
33 |
| SEUGI |
2001 |
Web clickstream analysis to understand customer behaviour [presentation] |
Erika Blanc,
Paolo Giudici |
source |
21 |
| SEUGI |
2001 |
WebMining [presentation] |
Goncalo Abreu,
Pedro Marques |
source |
15 |
| SEUGI |
2001 |
What is missing in campaign management today? [presentation] |
Shaun Doyle |
source |
18 |
| SUGI |
2001 |
A Case Study in Data Warehousing and Data Mining Using the SAS System |
Mary K. Tucker |
source |
3 |
| SUGI |
2001 |
A Practical Introduction to the Power of Enterprise Miner |
Michael S. Lajiness |
source |
7 |
| SUGI |
2001 |
Predictive Modeling in the Insurance Industry Using SAS |
Terry J. Woodfield |
source |
5 |
| SUGI |
2001 |
Quality Design Based on SAS/EM |
Wenming Chen |
source |
4 |
| SUGI |
2001 |
Using SAS Enterprise Miner for Forecasting |
Kattamuri S. Sarma |
source |
6 |
| SCSUG |
2000 |
Extending the Data Warehouse: An Introduction to OLE DB |
S. David Riba |
|
8 |
| SESUG |
2000 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
7 |
| SESUG |
2000 |
The Use of SAS in Revenue Management and Related Applications at ANC Rental Corporation |
Chi Ip,
ANC Rental,
Fort Lauderdale |
source |
2 |
| SESUG |
2000 |
Underlying Construct Analysis (UCA): Where Individual Systems End and Human Systems Begin |
Alvin L. Killough |
source |
8 |
| SESUG |
2000 |
Using Data Mining Technology to Identify and Prioritize Emerging Opportunities for Mortgage Lending to Homeownership-Deficient Communities |
Mortgage Lending |
source |
10 |
| SESUG |
2000 |
Word Pro - JADE_OleDB.lwp |
S. David Riba |
source |
8 |
| NESUG |
2000 |
Data Mining of Market Knowledge in The Pharmaceutical Industry |
John J. Cohen,
C. Olivia Parr Rud |
|
4 |
| NESUG |
2000 |
Implementing An E-intelligence Information System In An Extremely Active Web Environment |
Gina Iosue |
|
4 |
| WUSS |
2000 |
Data Warehousing for Data Mining: A Case Study |
C. Olivia Parr Rud |
source |
9 |
| WUSS |
2000 |
Extending the Data Warehouse: An Introduction to OLE DB |
S. David Riba |
source |
8 |
| WUSS |
2000 |
Implementing An E-Intelligence Information System in An Extremely Axctive Web Environment |
Gina Iosue |
source |
4 |
| MWSUG |
2000 |
Extending the Data Warehouse: An Introduction to OLE DB |
S. David Riba |
|
9 |
| MWSUG |
2000 |
Pharmaceutical Application of SAS Enterprise Miner |
Thomas H. Burger,
Jerry E. Plaatje,
John M. LaBore,
James K. Malone |
|
5 |
| MWSUG |
2000 |
Removing Slag to Get the Ore: Preparing Data for Mining |
Thomas H. Burger,
Jerry E. Plaatje,
John M. LaBore |
|
4 |
| SEUGI |
2000 |
Analysing the footprints of your customer - A case study by ask|net and SAS [presentation] |
Klaus-Peter Huber |
source |
40 |
| SEUGI |
2000 |
Automating the Information Supply Chain [presentation] |
Allan Russell,
Ben Zenick,
Robert Owen |
source |
42 |
| SEUGI |
2000 |
Churn in a Prepaid Cellular Market [presentation] |
Marcelle Georgiev,
Mohan Namboodiri |
source |
23 |
| SEUGI |
2000 |
Churn Prediction - The important element in the retention process [presentation] |
Gerhard Wanek |
source |
15 |
| SEUGI |
2000 |
Combining education and training to develop a new breed of SAS consultant: the SAS MSc in Business Intelligence [presentation] |
William Wallace |
source |
33 |
| SEUGI |
2000 |
Creating Strategic Advantage through Customer Knowledge Management [presentation] |
Andrew Thornton |
source |
27 |
| SEUGI |
2000 |
Credit Scoring with Enterprise Miner [presentation] |
Henrik Wagner |
source |
29 |
| SEUGI |
2000 |
CRM Out of the Box - An Integrated Turnkey Solution [presentation] |
Frank Block |
source |
25 |
| SEUGI |
2000 |
Data Mining and e-intelligence - A winning team [presentation] |
Gerhard Held,
Turlough Fitzpatrick |
source |
20 |
| SEUGI |
2000 |
Data Mining: Churn Management and Client Retention in Telecommunications [presentation] |
Lori Caton |
source |
20 |
| SEUGI |
2000 |
Data Warehouse in the Pocket - information you need on a GSM terminal [presentation] |
Atilla Papp,
Eva Torda |
source |
23 |
| SEUGI |
2000 |
Delivering improved risk management, sales reporting, targeting and campaign management using SAS and Intrinsic software in Banking [presentation] |
Shaun Doyle |
source |
20 |
| SEUGI |
2000 |
Deutche Bank: On-line banking for profit [presentation] |
Resi Cuypers |
source |
32 |
| SEUGI |
2000 |
E-Intelligence - through an Information Portal on the company intranet [presentation] |
Johan Jerresand |
source |
47 |
| SEUGI |
2000 |
e-Warehousing with SPD Server [presentation] |
Leigh Bates |
source |
31 |
| SEUGI |
2000 |
E=(DM)2 - The implementation a Business Intelligence Factory in the most Efficient and Effective Manner [presentation] |
Guido Cuzzocrea,
Italo Cattaneo,
Massimo Saputo |
source |
28 |
| SEUGI |
2000 |
Enhance SAP step-by-step with Customer Relationship Management Functionality [presentation] |
Patrick Schünemann |
source |
21 |
| SEUGI |
2000 |
Enterprise Mineer vs Underlying SAS Code: A Performance Comparison [presentation] |
Usama Hasan |
source |
11 |
| SEUGI |
2000 |
From Doctor Shopping to Data Warehouseing to Improve Health Outcomes [presentation] |
John Trabinger |
source |
47 |
| SEUGI |
2000 |
From the client datamart to the corporate data warehouse [presentation] |
Daniel Csikos |
source |
19 |
| SEUGI |
2000 |
Genetic Data Analysis with Enterprise Mineer [presentation] |
John C. Brocklebank,
Wayne Thompson |
source |
24 |
| SEUGI |
2000 |
HR Vision: The Power to Know your Workforce [presentation] |
Betty Silver |
source |
56 |
| SEUGI |
2000 |
Implementing An E-intelligence Information System In An Extremely Active Web Environment [presentation] |
Christopher A. Roper |
source |
20 |
| SEUGI |
2000 |
Information Delivery with SAS at Toyota [presentation] |
Dave Bullock,
Michael Eksteen |
source |
18 |
| SEUGI |
2000 |
Insurance Rate Making Using Data Mining [presentation] |
Bernd Drewes |
source |
50 |
| SEUGI |
2000 |
IT Service Vision - WebHound - Performance Tuning and Reporting [presentation] |
Don Koch,
Freda Cameron |
source |
42 |
| SEUGI |
2000 |
Mining in Melodies [presentation] |
Bulcsu Fajszi,
Laszlo Surjan |
source |
19 |
| SEUGI |
2000 |
New Features in Enterprise Miner [presentation] |
Gerhard Held,
John C. Brocklebank |
source |
30 |
| SEUGI |
2000 |
Retail & E-tailing: From Customer Understanding to Target Marketing [presentation] |
Bernd Drewes |
source |
49 |
| SEUGI |
2000 |
SAS can do it - now what did you want and how did you want it? |
Alyson Cromar,
Richard Coleman |
source |
6 |
| SEUGI |
2000 |
Successful and Faster Drug Development through Data Mining [presentation] |
Dirk Belmans |
source |
15 |
| SEUGI |
2000 |
Targeted Drug Discovery through Data Mining [presentation] |
John C. Brocklebank,
Wayne Thompson |
source |
28 |
| SEUGI |
2000 |
V8 Information Visualisation Enhancements [presentation] |
Stuart A. Nisbet |
source |
17 |
| SEUGI |
2000 |
Version 8 OLAP [presentation] |
Adrian Bruty |
source |
40 |
| SEUGI |
2000 |
Web Mining [presentation] |
Henrik Wagner |
source |
26 |
| SEUGI |
2000 |
Xelector: Select Connect Enable [presentation] |
Donnie O'Sullivan |
source |
23 |
| SUGI |
2000 |
Configuring and Optimizing Scalable Performance Data Server on HP-UX - A Performance Achievement |
Udo Schmitt |
source |
2 |
| SUGI |
2000 |
Data Warehousing for Data Mining: A Case Study |
C. Olivia Parr Rud |
source |
9 |
| SUGI |
2000 |
Data Warehousing for Manufacturing Yield Improvement |
Robert A. Rutledge |
source |
10 |
| SUGI |
2000 |
Enterprise Application Integration: Integration and Utilization of SAS Products |
Matthew K. Hettinger |
source |
6 |
| SUGI |
2000 |
Enterprise Integration Technologies - What Is It and What Can It Do for Me? |
Scott Vodicka |
source |
2 |
| SUGI |
2000 |
Production-Strength Data Mining Environment for Terabyte-Class Relational Data Warehouses |
Michael K. Nichols,
John Zhao,
John David Campbell |
source |
|
| SUGI |
2000 |
Using Enterprise Miner to Explore and Exploit Drug Discovery Data |
Michael S. Lajiness |
source |
8 |
| SESUG |
1999 |
An Introduction to the Next Big Thing: Parallel Computing |
John E. Bentley |
source |
10 |
| SESUG |
1999 |
Building Yield Management - GUI System at Norwegian Cruise Line by Using SAS/EIS and SAS/AF |
Sam Sheng |
source |
4 |
| SESUG |
1999 |
CRM 101: Maximizing Return on Investment with the SAS Solution for CRM |
Drury Jenkins |
source |
5 |
| SESUG |
1999 |
Tessera Rapid Modeling Environment: Production-Strength Data Mining Solution for Terabyte-Class Relational Data Warehouses |
Michael Nichols,
John Zhao,
John David Campbell |
source |
9 |
| WUSS |
1999 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
6 |
| SEUGI |
1999 |
A data model for database marketing activity |
Alberto Saccardi,
Frank Fiocca |
source |
2 |
| SEUGI |
1999 |
Comparison of various statistical techniques to support market retention and acquisition programs [presentation] |
Ian Thornhill |
source |
66 |
| SEUGI |
1999 |
Customer relationship management: organise for maximum ROI (Return on Information) |
Lynette Stassen |
source |
13 |
| SEUGI |
1999 |
Data mining methodoligies for business: cross selling [presentation] |
Henrik Wagner |
source |
37 |
| SEUGI |
1999 |
Data mining methodologies for business: fraud detection [presentation] |
Bernd Drewes |
source |
22 |
| SEUGI |
1999 |
Data mining technologies for business: an overview [presentation] |
Gerhard Held,
Gloria Miller |
source |
30 |
| SEUGI |
1999 |
Data warehouse architecture for model development [presentation] |
David Annis,
Turlough Fitzpatrick |
source |
32 |
| SEUGI |
1999 |
Data warehousing and cost management in the manufacturing sector using SAS System |
Nicolas Radulovic,
Ricardo Olea |
source |
7 |
| SEUGI |
1999 |
Database marketing simplified through data mining |
Arnfried Ossen |
source |
7 |
| SEUGI |
1999 |
Exploiting SAS/AF server models from SAS and COM clients [presentation] |
Robert Owen |
source |
69 |
| SEUGI |
1999 |
Forecasting Cross-Sectional Time Series: A Data Mining Approach Using Enterprise Miner Software |
John C. Brocklebank,
Michael Leonard,
Taiyeong Lee |
source |
3 |
| SEUGI |
1999 |
Insurance application: marketing database, forecasting model and cluster design at Reale Mutura Assicurazioni |
Flavio Bonifacio |
source |
16 |
| SEUGI |
1999 |
Integrating data mining and marketing campaign management technologies [presentation] |
Kurt Thearling |
source |
33 |
| SEUGI |
1999 |
Internet as an evolutionary tool of the information system [presentation] |
Giovanni Maio |
source |
30 |
| SEUGI |
1999 |
New product marketing analysis and launch [presentation] |
Jose Manuel Rey |
source |
80 |
| SEUGI |
1999 |
Quality assurance and SAS Application Development |
B. Dudink,
A. Geerts,
I. König,
M. Klijn,
E. Lekkerkerker-Smit |
source |
8 |
| SEUGI |
1999 |
SAS Applications in the exploring of life beginning data |
Jan Andrzej Domitrz,
Magdalena Topczewska |
source |
4 |
| SEUGI |
1999 |
SAS Enterprise Miner templates for database marketing applications |
Federico Ambrogi,
Guido Cussocrea,
Massimo Saputo |
source |
6 |
| SEUGI |
1999 |
Scalable data warehousing: storage users and more [presentation] |
Karin Edwards |
source |
40 |
| SEUGI |
1999 |
The squaring of the circle: managed health care - integration of medicine and economy [presentation] |
Georg A. Mathis,
Guido Schaub |
source |
26 |
| PharmaSUG |
1999 |
Data mining in The Pharmaceutical Industry |
John J. Cohen |
|
4 |
| SUGI |
1999 |
A SAS/AF Application for Parallel Extraction, Transformation, and Scoring of a Very Large Database |
Daniel Kohn,
David Kuh |
source |
7 |
| SUGI |
1999 |
Adding the Where to the Who |
Barry Hicks,
Rob Stephens,
Sanford Gayle,
Jack Bulkley |
source |
3 |
| SUGI |
1999 |
An Investigation of Quality-of-Life Issues in Patient Treatment Using Enterprise Miner |
Patricia B. Cerrito,
Kelly McMasters,
Vicki Viar |
source |
6 |
| SUGI |
1999 |
CRM 101: Maximizing Return on Investment with the SAS Solution for CRM |
Drury Jenkins |
source |
5 |
| SUGI |
1999 |
Forecasting Cross-Sectional Time Series: A Data Mining Approach Using Enterprise Miner Software |
John C. Brocklebank,
Michael Leonard,
Taiyeong Lee |
source |
3 |
| SUGI |
1999 |
Just Enough Database for Manufacturing Yield Analysis |
Robert A. Rutledge,
Linda H. Tai,
Garth W. Helf |
source |
6 |
| SUGI |
1999 |
Knowledge Management-Integrated Solutions for Information Delivery |
Kimberly A. Foster |
source |
8 |
| SUGI |
1999 |
Use of Enterprise Miner and Multivariate Statistical Analysis to Build Fraud-Detection Models |
Shiao-Ping Lu |
source |
5 |
| SUGI |
1999 |
Using SAS/INSIGHT Software as an Exploratory Data Mining Platform |
Robin Way |
source |
6 |
| WUSS |
1998 |
Data Warehouses and Bayesian Analysis - A Match Made by SAS |
Ram Gopalan |
source |
6 |
| WUSS |
1998 |
Use of Data Enterprise Miner & Multivariate Statistical Analysis to Build Fraud-Detection Models |
Shiao-Ping Lu |
source |
7 |
| NESUG |
1998 |
Data Mining: An Overview of Methods and Techniques for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
|
8 |
| NESUG |
1998 |
Fat Clients - Thin Clients: Stop the Madness |
Robert Szczerba |
|
4 |
| SEUGI |
1998 |
Data mining as a tool for Customer Selection [presentation] |
André Hønsvall,
Nils F. Haarvardsson |
source |
20 |
| SEUGI |
1998 |
Database marketing applications in the Italian banking sector |
Alberto Saccardi,
Guido Cuzzocrea |
source |
8 |
| SEUGI |
1998 |
How do you manage 2000 state policemen using advanced management information systems? [presentation] |
Danny Donnen |
source |
12 |
| SEUGI |
1998 |
Knowledge Discovery and Data Mining on the Example of Clinical Databases |
Leon Bobrowski,
Magdalena Topczewska |
source |
6 |
| SEUGI |
1998 |
Maximising the lifetime value of chosen customers: Closing the Loop [presentation] |
Chris Thompson |
source |
20 |
| SEUGI |
1998 |
Rapid business benefit for customer relationship management through data warehousing and data mining |
Nigel Wigram |
source |
12 |
| SEUGI |
1998 |
SAS data mining and neural networks: Powerful and efficient tools for customer-oriented pricing and target marketing in deregulated insurance markets |
Stefan Lecher |
source |
8 |
| SEUGI |
1998 |
SAS software within the Ernst & Young audit practice [presentation] |
Ton Buffing |
source |
36 |
| SUGI |
1998 |
Data Mining and Decision Support for Operational Problems Solutions in the Railroad Industry |
Pavel Brusilovskiy,
Robert Hernandez |
source |
7 |
| SUGI |
1998 |
Dun &Bradstreet: Using SAS Software to Solve Customer Purchasing Problems |
Christine C. Kelly,
Michael B. Smart |
source |
6 |
| SUGI |
1998 |
Finding the Solution to Data Mining: A Map of the Features and Components of SAS Enterprise Miner Software Table of Contents |
John C. Brocklebank,
Mark Brown |
source |
24 |
| SUGI |
1998 |
How SAS Has Impacted History or A 25 Y ear A f fair with the Semicolon |
James E. Duarte |
source |
4 |
| SUGI |
1998 |
Mining the Data Mart: A Case Study with Stock Market Data |
James A. Cox,
Tonya L. Etchison |
source |
11 |
| SUGI |
1998 |
Strategic Use of the SAS System in Banking |
Laurie Rose |
source |
5 |
| SUGI |
1998 |
Understanding Face Value - Giving Users What They Want... and Still Meeting Their Needs |
Kimberly A. Foster |
source |
6 |
| SCSUG |
1997 |
Applications of Intelligent Technologies for Efficient Businesses |
D. Thomas Taylor,
Ron Salazar |
|
6 |
| SCSUG |
1997 |
Internet Breast Cancer Education: Application of JMP Software in the Analysis |
Jeanette Rasche,
Shane Story,
Jeremy Wise,
James Zadinsky |
|
9 |
| PNWSUG |
1997 |
Using SAS/Insight as an Introductory Data Mining Platform |
Robin E. Way |
|
7 |
| PNWSUG |
1997 |
Why Business Intelligence is Being Asked to Demonstrate a Return on Investment |
John McIntyre |
|
3 |
| WUSS |
1997 |
SAS/SPECTRAVIEW Software and Data Mining: A Case Study |
Stuart Nisbet,
Ronald E. Stogner,
Aaron Hill |
source |
5 |
| NESUG |
1997 |
Digging For Gold: Business Usage for Data Mining |
Kimberly A. Foster |
|
6 |
| NESUG |
1997 |
Mining Your Data for Health Care Quality Improvement |
Greg Rogers |
|
7 |
| SESUG |
1997 |
SAS/SPECTRAVIEW Software and Data Mining: A Case Study |
Ronald E. Stogner |
|
5 |
| SEUGI |
1997 |
A customer MIS in banking |
Dominique Rudin |
source |
18 |
| SEUGI |
1997 |
Data Mining and SAS/SPECTRAVIEW software: a case study |
Annie Postic,
Bengt Bengtsson |
source |
36 |
| SEUGI |
1997 |
Experience gained implementing a data warehouse at a large retail company |
Anders Lissola |
source |
6 |
| SEUGI |
1997 |
The benefits of data warehousing in Holmia |
Staffan Wadström |
source |
39 |
| SEUGI |
1997 |
The development of enterprise information systeme |
Imrich Weigl,
Stanislav Klabník |
source |
12 |
| SEUGI |
1997 |
The future of data warehousing |
Sean Kelly |
source |
28 |
| SUGI |
1997 |
A SAS Based Data Mining Approach to Find Database Solutions in the Banking Industry |
Rama Jampani |
source |
2 |
| SUGI |
1997 |
Data Mining |
Mark Brown,
John C. Brocklebank |
source |
4 |
| SUGI |
1997 |
Data Mining for Hidden Groups in Hospital Populations |
Anthony M. Dymond |
source |
6 |
| SUGI |
1997 |
Mining Your Data for Health Care Quality Improvement |
Greg Rogers,
Ellen Joyner |
source |
7 |
| SUGI |
1997 |
SAS/SPECTRAVIEW Software and Data Mining: A Case Study |
Ronald E. Stogner,
Aaron Hill |
source |
5 |
| SUGI |
1997 |
Understanding Face Value - Giving Users What They Want... and Still Meeting Their Needs |
Kimberly A. Foster |
source |
5 |
| SCSUG |
1996 |
Why Knowing About Our Customers Helps Our Business |
Mark Brown |
|
4 |
| NESUG |
1996 |
Building Efficient Data Warehouses: Understanding the Issues of Data Summarization and Partitioning |
Robert Chu,
Susan Tideman |
|
8 |
| MWSUG |
1996 |
Building Efficient Data Warehouses: Understanding the Issues of Data Summarization and Partitioning |
Susan Tideman,
Robert Chu |
|
8 |
| WUSS |
1996 |
Preliminary Data Mining for Subgroups in a Hospital Inpatient Population |
Anthony M. Dymond |
source |
6 |
| SEUGI |
1996 |
An overview of data mining with the SAS System |
Gerhard Held |
source |
29 |
| SEUGI |
1996 |
Building an efficient data warehouse: understanding the issues of data summarization and ... |
Scott Anderson |
source |
52 |
| SUGI |
1996 |
Building an Efficient Data Warehouse: Understanding the Issues of Data Summarization and Partitioning |
Robert Chu,
Susan Tideman |
source |
8 |
| SUGI |
1996 |
Database Marketing and Business Geographies |
Mark Brown,
Jack Bulkley |
source |
6 |
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