Knowledge and Density Based Fuzzy-neuro Model for Collaborative Filtering Recommender Systems

Recommender systems are one of the information filtering systems which provides business intelligence to the active users on e-commerce by more suggesting suitable items through personalized web page. User’s explicit knowledge about the items, preferences, density of neighbours and recommendation criteria play vital role in providing accurate recommendations. This paper introduces knowledge and density based Fuzzy-Neuro model for personalized recommender system. Several experiments have been carried out to evaluate the performance of the model with different factors and evaluation measures. The experimental results show that the proposed model outperforms the conventional models.