Implicit: a recommender system that uses implicit knowledge to produce suggestions

The number of accessible web pages in Internet increases every day and it becomes very difficult to deal with such a huge source of information. There exist several approaches aimed to provide user with high-quality links extracted from the thousands of irrelevant ones. We present a system Implicit that combines recommender system and multi-agent system approaches and is intended to be used within community of people with similar interests. It produces suggestions by using implicit knowledge of the members of a community and complementing these suggestions with results from search engines. Agents within the system interact one another and share knowledge in order to increase quality of the recommendations by using similarities in the behavior of different users.