Abstract:
Nowadays, recommender systems have been used to
reduce information overload and to find the items that
are of interest to the user. Many techniques have been
proposed for providing recommendations to consumers
or users. All currently available recommender
techniques have strengths and weaknesses. Thus,
numerous researcher studies have attempted to develop
techniques that would overcome the various limitations
of current recommender systems by combining existing
techniques in different ways. On the other hand, we
have found that many currently available recommender
systems are still designed for some restricted domains.
This paper presents our attempt to use agent technology
to enhance recommender systems based on agent’s
property advantages with the goal to analyze and
design a general architecture easily adaptable to
several domains
