The ongoing rapid expansion of the Internet greatly increases the necessity of effective
recommender systems for filtering the abundant information. Extensive research for …

Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …

Recommender systems use data on past user preferences to predict possible future likes
and interests. A key challenge is that while the most useful individual recommendations are …

Predictions of missing links of incomplete networks, such as protein-protein interaction
networks or very likely but not yet existent links in evolutionary networks like friendship …

Complex networks have emerged as a simple yet powerful framework to represent and
analyze a wide range of complex systems. The problem of ranking the nodes and the edges …

Complex networks such as the Internet, WWW, transportation networks, power grids,
biological neural networks, and scientific cooperation networks of all kinds provide …

Identifying the node spreading influence in networks is an important task to optimally use the
network structure and ensure the more efficient spreading in information. In this paper, by …

Personalized recommender systems are confronting great challenges of accuracy,
diversification and novelty, especially when the data set is sparse and lacks accessorial …

Based on the user-tag-object tripartite graphs, we propose a recommendation algorithm that
makes use of social tags. Besides its low cost of computational time, the experimental results …

In this paper, based on a weighted object network, we propose a recommendation
algorithm, which is sensitive to the configuration of initial resource distribution. Even under …