Real networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify vital nodes is thus very significant, allowing us to control …

Complementary to the fancy applications of social networks, influence analysis is an
indispensable technique supporting these practical applications. In recent years, this …

In the modern e-commerce, the behaviors of customers contain rich information, eg,
consumption habits, the dynamics of preferences. Recently, session-based …

With the advent and popularity of social network, more and more users like to share their
experiences, such as ratings, reviews, and blogs. The new factors of social network like …

Social influence analysis has become one of the most important technologies in modern
information and service industries. Thus, how to measure social influence of one user on …

Influence maximization, defined by Kempe et al.(SIGKDD 2003), is the problem of finding a
small set of seed nodes in a social network that maximizes the spread of influence under …

Exponential growth of information generated by online social networks demands effective
recommender systems to give useful results. Traditional techniques become unqualified …

This chapter provides an accessible introduction for point processes, and especially Hawkes
processes, for modeling discrete, inter-dependent events over continuous time. We start by …

Twitter has rapidly grown to a popular social network in recent years and provides a large
number of real-time messages for users. Tweets are presented in chronological order and …

With the rapidly growing location-based social networks (LBSNs), personalized geo-social
recommendation becomes an important feature for LBSNs. Personalized geo-social …