Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior
Proceedings of the 2nd ACM conference on Electronic commerce
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
The Knowledge Engineering Review
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
A generic framework for comparing semantic similarities on a subsumption hierarchy
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Distributed semantic search for the web: a multiagent approach
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Engineering self-organizing referral networks for trustworthy service selection
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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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.