A Novel Recommender Model Using Trust Based Networks

Recommended systems are highly rated recently by online users in social networking. In general, recommendation model made by existing algorithms are not reliable because these recommendations did not consider the trust factor between active users and nearest neighbors in social networks services. In order to solve this problem, new methods have been suggested based on trust-based networks with missing connections among users and elimination of cold start scenario. In our study, experiments are conducted on publicly available datasets to validate our algorithm. Through experimental results, our model is proven more robust, efficient in execution and more precise.