In this paper, we presents a new blog recommender based on the hyper graph modeling
clustering algorithm. The algorithm of this system is called multilevel clustering segmentation …

The distribution of the number of items liked by users plays an important role in designing
recommender systems. In case of implicit feedback we rarely get some clicking events …

Content in microblogging systems is produced by hundreds millions of people and is
definitely becoming a huge internet resource repository now. Previous research on social …

Recommender system provides users with personalized suggestions of product or
information. Typically, recommender systems rely on a bipartite graph model to capture user …

Blogs are a new form of internet phenomenon and a vast ever-increasing information
resource, which are dated unedited, highly opinionated personal online commentary …

In order to improve the recommendation accuracy, it is important to use a variety of models
that compensated for each other's shortcomings. In this paper, we propose a hybrid …

With the rapid growth of the World Wide Web, many efforts have been done to address the
problem of information overload. Recommender systems help users make decisions in this …

Microblogging has created a big social network with big social media data. Modeling and
analyzing the relationships of behaviors among micro log users, and achieving the inherent …

The purpose of the research paper is to analyze the characteristics of users in social
networking Web sites as well as the related contents of the Web sites. This research expect …

The rapid growth of weblog provides a rich resource for social community mining. In this
paper, we put forward a novel research problem of recommendation under the circumstance …