Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative fil...
Collaborative Filtering, considered by many researchers as the most important technique for information filtering, has been extensively studied by both academic and industrial co...