Eric Siegel

Published Papers

Book on Predictive Analytics

• Eric Siegel, Ph.D., Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Wiley, 2013. This rich, entertaining primer by former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of predictive analytics, showing how predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime-fighting, and boosts sales.

Tutorials on Data Mining, Predictive Modeling and CRM Analytics

• Eric Siegel, Ph.D., "Uplift Modeling: Predictive Analytics Can't Optimize Marketing Decisions Without It," White paper produced by Prediction Impact and sponsored by Pitney Bowes Business Insight, June, 2011.
• Eric Siegel, Ph.D., "If you can predict it, you own it: Four steps of predictive analytics to own your market," SAS Business Analytics Knowledge Exchange, June 2011.
• Eric Siegel, Ph.D., "Seven Reasons You Need Predictive Analytics Today," White paper produced by Prediction Impact and sponsored by IBM, September, 2010.
• Eric Siegel, Ph.D., "Six Ways to Lower Costs with Predictive Analytics ," BeyeNETWORK, January, 2010.
• Eric Siegel, Ph.D., "Casual Rocket Scientists: An Interview with a Layman Leading the Netflix Prize," Predictive Analytics World, September, 2009.
• Eric Siegel, Ph.D., "Predictive Analytics Delivers Value Across Business Applications," (or see the less spiffy whitepaper version) BeyeNETWORK, January, 2009.
• Eric Siegel, Ph.D., "Predictive analytics for revenue-generating response models," DMNews, January, 2008.
• Eric Siegel, Ph.D., "Predictive Analytics' Killer App: Retaining New Customers," DM Review Magazines Extended Edition, February, 2007.
• Eric Siegel, Ph.D., "Predictive Analytics with Data Mining: How it Works," (or see the less spiffy white paper version) DM Review Magazine's DM Direct, February, 2005.
• Eric Siegel, Ph.D., "Driven with Business Expertise, Analytics Produces Actionable Predictions," CRM Magazine's DestinationCRM, March, 2004.
• Eric Siegel, Ph.D., "Analytics + Business Expertise = Actionable Predictions for Each Customer," Prediction Impact white paper, 2004.

CS EDUCATION PUBLICATIONS

• Siegel, Eric V. ``Iambic IBM AI: The Palindrome Discovery AI Project.'' 31st Technical Symposium of the ACM Special Interest Group in Computer Science Education, Austin, TX: March, 2000. [abstract, full paper]
  
  
• Siegel, Eric V. ``Why Do Fools Fall Into Infinite Loops: Singing To Your Computer Science Class.'' 4th Annual Conference on Innovation and Technology in Computer Science Education (SIGCSE-sponsored), Cracow University of Economics, Cracow, Poland: June, 1999. [abstract, full paper]
  
  
• Eskin, E. and Siegel, Eric V. ``Genetic Programming Applied to Othello: Introducing Students to Machine Learning Research.'' 30th Technical Symposium of the ACM Special Interest Group in Computer Science Education, New Orleans, LA: March, 1999. [abstract, full paper]

RESEARCH PUBLICATIONS

• S. Robertson, E. Siegel, M. Miller, and S. Stolfo, ``Surveillance Detection in High Bandwidth Environments''. The Third DARPA Information Survivability Conference and Exposition (DISCEX III), Washington, D.C., April, 2003.
  
  
• Siegel, Eric V. and McKeown, Kathleen R. ``Learning Methods to Combine Linguistic Indicators: Improving Aspectual Classification and Revealing Linguistic Insights''. Computational Linguistics, December, 2000.
  
  
• Siegel, Eric V. ``Corpus-Based Linguistic Indicators for Aspectual Classification''. Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, University of Maryland, College Park, MD, June, 1999. [abstract, full paper]
  
  
• Siegel, Eric V. ``Disambiguating Verbs with the WordNet Category of the Direct Object''. Usage of WordNet in Natural Language Processing Systems Workshop, Universite de Montreal, August, 1998. [abstract, full paper]
  
  
• Siegel, Eric V. Linguistic Indicators for Language Understanding: Using machine learning methods to combine corpus-based indicators for aspectual classification of clauses. Ph.D. Dissertation, 1998. Committee: Kathleen R. McKeown (Advisor), John R. Kender, Judith Klavans, Philip Resnik, Sal Stolfo [abstract, acknowledgements,, full paper]
  
  
• Siegel, Eric V. ``Learning methods for combining linguistic indicators to classify verbs''. Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, Providence, RI: August, 1997. [abstract, full paper]
  
  
• Siegel, Eric V. and Chaffee, Alexander D. ``Genetically optimizing the speed of programs evolved to play Tetris''. In Advances in Genetic Programming: Volume 2, edited by P.J. Angeline and K. Kinnear, MIT Press, Cambridge, MA: 1996. [abstract, full paper]
  
  
• Siegel, Eric V. and McKeown, Kathleen R. ``Gathering statistics to aspectually classify sentences with a genetic algorithm''. In Proceedings of the Second International Conference on New Methods in Language Processing, Ankara, Turkey: Sept. 1996. [abstract, full paper]
  
  
• Siegel, Eric V. and Koza, John R., editors. Genetic Programming: Papers from the AAAI Fall Symposium, AAAI Technical Report FS-95-01, Cambridge, MA: 1995. [contents]
  
  
• Siegel, Eric V. ``Competitively evolving decision trees against fixed training cases for natural language processing''. In Advances in Genetic Programming, edited by K. Kinnear, MIT Press, Cambridge, MA: 1994. [abstract, full paper]
  
  
• Siegel, Eric V. and McKeown, Kathleen R. ``Emergent linguistic rules from inducing decision trees: disambiguating discourse clue words''. In Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA: July 1994. [abstract, full paper]
  
  

Also see: some editorial comments and more reference info on my genetic programming papers, as listed in the genetic programming bibliography.

email: evs at cs dot columbia dot edu