Rapid growth in the amount of data available on social networking sites has made information retrieval increasingly challenging for users. In this paper, we propose a collaborativ...
Matrix factorization is a successful technique for building collaborative filtering systems. While it works well on a large range of problems, it is also known for requiring signi...
Alexandros Karatzoglou, Alexander J. Smola, Markus...
In recommender systems, user ratings of items are often represented in terms of linguistic labels such as “fair” or “very good”. We investigate the potential of fuzzy sets...
In this paper, we propose an information retrieval model called Latent Interest Semantic Map (LISM), which features retrieval composed of both Collaborative Filtering(CF) and Prob...
Abstract. Understanding the collaborations that arise between the instances of classes in object-oriented programs is important for the analysis, optimization, or modification of ...
Stephanie Balzer, Thomas R. Gross, Patrick Eugster