In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Collaborative filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. Such techniques recommend products to customers using similar users...
Abstract. Many current recommender systems exploit textual annotations (tags) provided by users to retrieve and suggest online contents. The text-based recommendation provided by t...
Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, ...
This paper describes a technique for making personalized recommendations from any type of database to a user based on similarities between the interest pro le of that user and tho...