Abstract

On the world wide web, there\'s need to filter, prioritize and effectively deliver pertinent data so as to alleviate the\nproblem of information overload, which has made a possible problem to many Internet users. Recommender systems solve\nthis issue by searching through large volume of dynamically generated information to provide users with personalized\ncontent and solutions. Recommender systems are information filtering systems which manage the problem of information\noverload by filtering vital info fragment out of substantial amount of dynamically generated information according to user\'s\npreferences, attention, or observed behaviour about item. Recommender system has the power to predict if a specific user\nwould prefer an item or not based on the consumer\'s profile. The current function combines the methods for Fuzzy Clustering\nand Voting theory approaches in order to design an efficient Recommender System.