The large amount of available information on the Web makes hard for users to locate resources about their information needs. The conventional search tools do not always successfully cope with this problem and, for this reason, the personalized search systems are receving increasingly attention, as a well-founded alternative to cope with this problem.
We present an adaptive and scalable Web search system, based on a multi-agent reactive architecture, which drew inspiration from biological researches on the ant foraging behavior. Its target is to search autonomously information on particular topics, in huge hypertextual collections, such as the Web, exploiting the outstanding properties of the agent architecture. The algorithm has proven to be robust against environmental alterations and user information need changes, discovering valuable results from standard Web collections.
- MICARELLI A., GASPARETTI F.. Adaptive Focused Crawling. In Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.): The Adaptive Web: Methods and Strategies of Web Personalization. Volume 4321 of Lecture Notes in Computer Science, pp.231-262, Springer-Verlag, Berlin Heidelberg New York, ISBN: 978-3-540-72078-2, 2007 (Preprint PDF, The original publication is available at www.springerlink.com) Bibtex.
- GASPARETTI F., MICARELLI A.. Swarm Intelligence: Agents for Adaptive Web Search. In Proc. of the 16th European Conference on Artificial Intelligence ECAI 2004, Valencia, Spain, 23-27 Agosto 2004 (Preprint PDF) Bibtex.
- GASPARETTI F., MICARELLI A.. Adaptive Web Search Based on a Colony of Cooperative Distributed Agents. In Proc. of the Cooperative Information Agents VII, 7th International Workshop, CIA 2003, pp.168-183, Helsinki, Finland, 27-29 August 2003. Bibtex