 Accenture
161 North Clark St.
Chicago IL 60601
USA
Research Interests Machine learning and information extraction, open-domain question
answering, knowledge representations, programming languages.
Recent Projects
I've been involved in a retail project targeted at grocery stores. It
explored shopping behavior and how to predict shopping lists for a given trip
from purchase history. Individual Consumer Modeling (with Andrew Fano, Rayid Ghani and Marko Krema ): This project is aimed at using customer purchase data from retailers to create individual consumer models that are able to detect and predict the behaviors of customers with respect to their shopping. These consumer models enable the retailer to provide customers with individual and personalized interactions as they navigate through the retail store. Instead of using traditional personalization approaches, such as clustering or segmentation, we learn separate classifiers and statistical models for each customer using historical transactional data only from that customer. This allows us to make very fine, accurate predictions about a particular individual customer during a shopping trip. The research challenges include learning and evaluation metrics with a very large number of categories, noisy data sources and concept drift over time. See paper on Predicting Shopping Lists at KDD 2004, and Intelligent Shopping Assistants at IUI 2005. Intelligent Promotion Planning (with Andrew Fano, Rayid Ghani and Marko Krema): The Intelligent Promotion Planning is a prototype that enables retailers and product manufacturers to industrialize the use of individual consumer models in offering personalized promotions. It offers an environment to visualize and interact with past data about product promotions as well as tools to explore and implement future promotions. There is an optimization capability, where optimal parameters of the promotion are selected based on high-level goals set by the retailer, as well as a simulation environment where a lot of what-if scenarios could be considered and the results of a potential promotion evaluated before implementation.
Selected Publications
Learning Individual Consumer Models for Personalized Promotions: A Data Mining Case Study. Chad Cumby, Andrew Fano, Rayid Ghani and Marko Krema
Workshop on Data Mining for Business - held with the European Conference on Machine Learning (ECML/PKDD 2005). Building Intelligent Shopping Assistant Using Individual Consumer Models
C. Cumby,
A. Fano, R. Ghani and M. Krema
Proceedings of the 2005 International Conference on Intelligent User Interfaces
January 9-12, 2005
San Diego, California
[Abstract] [Paper PDF] Predicting Customer Shopping Lists from Point-of-sale Purchase Data
C. Cumby,
A.E. Fano, R. Ghani and M.
Krema
10th ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining
August 2004
Seattle, Washington
[Abstract] [Paper
(PDF)]
On Kernel Methods for Relational Learning
C. Cumby and D. Roth
International Conference on Machine Learning (ICML 2003)
August 21-24, 2003
Washington, DC Learning With Feature Description Logics
C. Cumby and D. Roth
International Conference on Inductive Logic Programming (ILP 2002)
July 9-12, 2002
Sydney, Australia
Education
- M.S., Computer Science, University of Illinois at Urbana-Champaign
- Mathematics and Computer Science, University of Illinois at Urbana-Champaign
Personal Interests
Music, home brewing, soccer and movies.
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