Agent Based Information Retrieavl System

The quantity of presentations on the Internet is constantly increasing. This implies the problem of searching and quickly retrieving the appropriate information. Several researches show that using intelligent agents in the information retrieval system is an efficient way to solve this problem. Different proposed systems use different types of agents. Some agents used to understand the user requirements. Others used to increase the performance. In this paper we propose a multi-agent based information retrieval system. The system can be used to search for long term interest as well as short term interest. We take the advantages of several techniques borrowed from the software engineering, artificial intelligence and information retrieval fields. The proposed system creates a user profile to understand the user long term interest. The profile is optimized with genetic algorithm and adapted with the relevance feedback. The user queries and the retrieved documents are analyzed with natural language processing techniques. We show how our proposed system increases both the network and information retrieval performance.