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Browse Prior Art Database

An information theoretic approach for customer modeling

IP.com Disclosure Number: IPCOM000015832D
Original Publication Date: 2002-Jul-20
Included in the Prior Art Database: 2003-Jun-21

Publishing Venue

IBM

Abstract

Abstract In this invention, we introduce a method for dynamically updating the customer profile. Individual customer profile is central to the personalization of B2C commerce. The merchant can derive a number of attributes from the customer’s demographics, purchase pattern and interests, e.g., whether or not a customer is loyal, flamboyant, extravagant and/or price-conscious. The derived attributes enable merchant to incorporate his/her business knowledge in the personalization system. Given the abstract nature of some of the derived attributes, it is difficult for a merchant to explicitly define the derived attributes. In this invention, we introduce a new adaptive method to model customer behavior, using information-theoretic criteria. Field of Invention: The invention, in general, is related to the field of personalization, and in particular, to the B2C (business to consumer) e-commerce. In this invention, a way of modeling the individual customer profile is introduced based on an information-theoretic measure. We propose a combination of supervised and unsupervised learning techniques to model the customer behavior.