Abstract
Millions of users search the Web every day to locate Web resources relevant to their interests. Unfortunately, the Web resources found by a user with a specific interest are usually not shared with others having the same or similar interests. In this paper, we propose an agent-based approach for collaborative distributed semantic search of the Web. Our approach enables a human user to semantically describe his search interest to an agent. Depending on the interests of their users, the agents evolve their vocabularies and create search concepts. Based on these search concepts, the agents discover other agents having similar search interests and collaborate with them to locate Web resources relevant to their search interests. Our empirical evaluations and the analysis of the proposed approach show that our approach enables agents with similar interests to coordinate and compose virtual communities. Within these communities, the agents interact to locate and share pointers to the Web resources relevant to the search interests of their users.
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Şensoy, M. (2012). Evolving Semantics for Agent-Based Collaborative Search. In: Dechesne, F., Hattori, H., ter Mors, A., Such, J.M., Weyns, D., Dignum, F. (eds) Advanced Agent Technology. AAMAS 2011. Lecture Notes in Computer Science(), vol 7068. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27216-5_36
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DOI: https://doi.org/10.1007/978-3-642-27216-5_36
Publisher Name: Springer, Berlin, Heidelberg
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