Factorizing personalized Markov chains for next-basket recommendation
WWW, pp. 811-820, 2010.
matrix factorizationmarkov chain
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn the general taste of a user by factorizing the matrix over observed user-item preferences. On the other hand, MC methods model sequential behavior by learning a...More
Best Paper of WWW, 2010