News Topic Recommendation Using an Extended Bayesian Personalized Ranking
Bayesian Personalized Ranking (BPR) is a recommendation approach which learns to rank candidate items based on user's implicit feedback. In this study I use an extended version of BPR using consumption behavior of user on news articles to recommend them news topics. The extended version of BPR performs better compare to the original version based on two evaluation measures.
BNAIC/BENELEARN