Agent-based support for personalized information with web search engines

The popularization of computers and the Internet has produced an explosion in the amount of information and makes it difficult to find them. In order to complement the works of Web agents for autonomously browsing or filtering on behalf of the user, we focus on adaptive agents for providing support at query formulation and information filtering. These adaptive or learning agents make it possible to add a layer of personalization and collaboration between the users and the existing search engines. The personalization is realized by learning the user preference and using it at query formulation and filtering, while the social aspect is obtained by exchange of information between agents with similar interests.