Intelligent Information Retrieval Model Based on Multi-Agents

Information Retrieval in the World Wide Web (WWW) using the general search engines is still a difficult and time-consuming task, which creates a demand of new information search and retrieval techniques. An intelligent retrieval system model based on multi-agent is proposed which assists the user in finding interesting information in the WWW. This model searches through the popular and special Web search engines, filters their result, and lists to the user a reduced number of information with high probability of being relevant to him. This filtering is implemented by the agent analyzing the user´s behavior on the Web based on user´s search intent and preferences. The design, the architecture, the functional components and the workflow of the model are elaborated. The model is helpful to solve the shortcomings effectively of low precision and relevant document ranking behind in general search engine.