Multi-view clustering (MVC) aims to fuse the information among multiple views to achieve
effective clustering. Many MVC algorithms based on semi-nonnegative matrix factorization …

Representation learning is an important topic in machine learning, pattern recognition, and
data mining research. Among many representation learning approaches, semi-nonnegative …

As one of the most successful recommendation techniques, collaborative filtering provides a
useful recommendation by associating an active user with a crowd of users who share the …

We present a new recommender system developed for the Russian interactive radio network
FMhost. To the best of our knowledge, it is the first model and associated case study for …

The matrix factorisation approach computes a low‐rank approximation of the incomplete
user‐item rating matrix. Existing approaches suffer from under‐fitting due to the use of global …

With the advent of Web 2.0, Social Computing has emerged as one of the hot research
topics recently. Social Computing involves the collecting, extracting, accessing, processing …

Learning to Recommend Page 1 Learning to Recommend MA, Hao A Thesis Submitted in Partial
Fulfilment of the Requirements for the Degree of Doctor of Philosophy in Computer Science and …

Collaborative filtering (CF) is a key technique in recommender system. Recently, general
neighborhood problem existing in collaborative filtering is identified in our previous work …

Heterogeneous transfer clustering can translate knowledge from some related
heterogeneous source domains to the target domain without any supervision. Existing works …

We present a new recommender system developed for the Russian interactive radio network
FMhost. The system aims to improve the quality of this service; it is designed specifically to …