Agent-Based Semantic Collaborative Search

Next generation of the Web builds upon technologies such as Semantic Web and Intelligent Software Agents. These technologies aim at knowledge representation that allows both humans and software agents to understand and reason about the content on the Web. In this paper, we propose an agent-based approach for collaborative distributed semantic search of the Web resources. 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 ontologies and create search concepts. Based on these search concepts, the agents coordinate and compose virtual communities. Within these communities, agents with similar interests interact to locate and share URLs relevant to search interests of their users. Through these interactions, shared vocabularies are cooperatively emerged by agents to communicate properly within the communities. Our empirical evaluations and analysis of the proposed approach show that our approach combines Semantic Web technologies and multi-agent systems in a novel way to enable users to find and share the URLs relevant to their search interests.