Recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. A predominant approach to collabo...
This paper proposes extending semi-supervised learning by allowing an ongoing interaction between a user and the system. The extension is intended to not only to speed up search fo...
: Recommender systems are widely used online to support users in finding relevant information. They can be based on different techniques such as content-based and collaborative ...
Katja Niemann, Maren Scheffel, Martin Friedrich, U...
: Skyline Queries have recently received a lot of attention due to their intuitive query capabilities. Following the concept of Pareto optimality all `best' database objects a...
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...