Trust-based New Recommendation Algorithm of Collaborative Filtering Combination
Yajun Liu, Lina Bao, Lisha Gao · 2014
Aimed at resulting accuracy for common single recommendation technology are not high and there are some limitations, trust relationship in sociology is introduced into personalized news recommendation. This article raises a trust-based new recommendation algorithm of collaborative filtering combination. First, it measures users’ trust to recommendation algorithm through the recommendation accuracy; then, in order to raise quality, the recommendation results of user-based and item-based collaborative filtering recommendation algorithm are combined through the trust. The experimental results show that trust-based combining recommendation algorithm have more accurately predict the degree of user interest in news than user-based and item-based collaborative filtering recommendation algorithm and more news of interest to recommend to the user, so it has the effect of better recommended.