An Adaptive Multi-Agent Architecture for the ProFusion* Meta Search System

The goal of this project is to develop an intelligent, adaptive Web search tool. Our work is based on ProFusion, a Web meta-search engine developed at the University of Kansas. ProFusion analyzes incoming queries, categorizes them, and automatically picks the best search engines for the query based on a priori knowledge (confidence factors) which represents the suitability of each search engine for each category. It uses these confidence factors to merge the search results into a re-weight list of the returned documents, removes duplicates and, optionally, broken links and presents the final rank-ordered list to the user. The main goals of the current research are to 1) provide ProFusion with a multi-agent architecture which is easier to extend, maintain and distribute and 2) to include automatic adaptation algorithms to replace the hard-coded a priori knowledge.