Creating recommendations on electronic books: A collaborative learning implicit approach
It is possible to develop more efficient recommender systems that does not depend on users explicit ratings. It is possible to determine users interest by analyzing and converting their behavior. This approach allows to build a collective web knowledge in a co-learning context. This work allows to analyze the users behavior data and convert it into explicit ratings. 75.6% of data obtained by the conversion mechanism is close to optimal values.
collaborative learning recommender system books recommendation implicit feedback