Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
A key element of the social networks on the internet such as Facebook and Flickr is that they encourage users to create connections between themselves, other users and objects. On...
Artus Krohn-Grimberghe, Lucas Drumond, Christoph F...
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...
Multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multipledimensional data summarization. Analyzing all the dimensions...