 Accenture
161 North
Clark St.
Chicago IL 60601
USA
Research Interests
Text classification, information extraction, web agents, and intelligent user interfaces. Recent Projects I am actively involved in the Machine Learning
and Data-Mining Group.
Currently working on a project on the thematic categorization of documents which allows both a better way of finding documents and a better understanding of the document space. My research focuses on identifying thematic categories that can be used to find information about a topic that is relevant to the task of the user. I also am involved in various projects in the information insight area. Attribute Extraction from Product Descriptions (with Andrew Fano, Rayid Ghani, Katharina Probst ): We are developing tools and algorithms for extraction of product attributes and values, such as size, material and other specifications from product descriptions. The tools are intended as enablers for a variety of applications including assortment planning, brand management and catalog mapping. Our methodology includes machine learning techniques for labeled and unlabeled data, natural language processing techniques and an active learning feedback loop that interactively refines the inferred hypotheses. Individual Consumer Modeling (with Chad Cumby, Andrew Fano, Rayid Ghani): This project is aimed at using customer purchase data from retailers to create individual consumer models that are able to detect and predict the shopping behaviors of customers. 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 an 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 Chad Cumby, Andrew Fano and Rayid Ghani): 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 Text Mining to Extract Product Attributes.
Rayid Ghani, Katharina Probst, Yan Liu, Marko Krema, and Andrew Fano.
SIGKDD Explorations (2006).
[Paper (PDF, 99K)]
PDF Help 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). J. Budzik, K. J. Hammond, L. Birnbaum, and M. Krema. Beyond Similarity. In Working notes of the AAAI 2000
Marko Krema, Larry Birnbaum, Jay Budzik, Kristian J. Hammond: Themometers and themostats: characterizing and controlling thematic attributes of information. IUI 2002: 196-197 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 of Building Intelligent Shopping Assistant using Indevidual Consumer Models]
[Paper (PDF)]
PDF Help 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 of Predicting Customer Shopping Lists from Point-of-sale Purchase Data] [Paper
(PDF)]
Education
- M.S., Computer Science, Northwestern University
- B.S., Computer Science and Mathematics
B.A. Philosophy, Baker
University
Personal Interests
Family, politics, movies, stories and story structure and video games.
 To Top
|