ACM Videos on Analytics and Data Mining

ACM Data Mining SIG: Ted Dunning on Mining Transactional Data

This talk presents effective feature extraction methods for mining transactional data elements. Transactional data are bags of large vocabulary categorical data that are optionally time-embedded.
This class includes textual data as a sub-class. By extending previous methods for feature extraction in textual settings, Dr. Ted Dunning has been able to define classes of feature extractors that work on a wide class of problems of significant practical import. These include profitability prediction in insurance, fraud detection in credit, recommendation based on implicit observation of web behavior and other areas.

Other relevant talks include

• The Facebook Era: Clara Shih
• Jeff Scargle: Optimal Segmentation Analysis of Event Data
• Dan Steinberg on Interaction Detection with TreeNet
• Michael Bowles: Neural Nets & Rule-Based Trading Systems
• Greg Makowski: Event Lift Forecasting