To appear in: Proceedings of 1999 AAAI Symposium on Intelligent Agents in Cyberspace, Stanford University, March 1999.
Adaptive Agents for Information Gathering from Multiple, Distributed Information Sources
Yizhong Fan and Susan Gauch
Electrical Engineering and Computer Science
415 Snow Hall
University of Kansas
Lawrence, KS 66045
sgauch@ittc.ku.edu
Abstract
The expansion of information available on the Web has been explosive. The initial approach of collecting
all Web pages into a single location and indexing them is limited in its ability to deal with this
explosion. Different search engines provide access to different collections, requiring users to access
multiple information sources to meet their needs. A scalable approach to information gathering from
multiple sources is described which is based on the use of distributed information agents to route
queries to the most appropriate sources and fuse information they provide. This paper describes an
intelligent, adaptive Web search tool that can not only locate relevant information sources for the
user, but also adapt to the frequent changes of the dynamic Web environment. We employ a multiple agent
architecture to intelligently categorize and broker queries to remote search engines, learn and
continuously update confidence factors for the quality of results provided by each search engine, and
automatically detect and adapt to changes in the syntax used by the search engines. Our work is an
extension of ProFusion http://www.profusion.com [Gauch 96a], a Web meta-search engine developed at the
University of Kansas which can currently broker information from nine remote search engines.
View Paper
If you have any comments, please send your comments to me.
sgauch@ittc.ku.edu.