Next-generation agent-enabled comparison shopping

Agents are the catalysts for commerce on the Web today. For example, compar ison-shopping agents mediate the interactions between buyers and sellers in order to yield more efficient markets. However, today's shopping agents ar e price-dominated, unreflective of the nature of seller/buyer differentiati on or the changing course of differentiation over time. This paper aims to tackle this dilemma and advances shopping agents into a stage where both ki nds of differentiation are taken into account for enhanced understanding of the realities. We call them next-generation shopping agents. These agents can leverage the interactive power of the Web for more accurate understandi ng of buyer's preferences. This paper then presents an architecture of the next-generation shopping agents. This architecture is composed of a Product /Merchant Information Collector, a Buyer Behavior Extractor, a User Profile Manager and an Online Learning Personalized-Ranking Module. We have implem ented a system following the core of the architecture and collected prelimi nary evaluation results. The results show this system is quite promising in overcoming the reality challenges of comparison shopping. (C) 2000 Elsevie r Science Ltd. All rights reserved.