With the widespread popularization of social network platforms, user-generated content and
other social network data are growing rapidly. It is difficult for social users to select interested …

In the literature, various collaborative filtering approaches have been developed to perform
an efficient recommendation on top of reducing the search cost of the customers. The …

With the massive growth of the internet, a new paradigm of recommender systems (RS's) is
introduced in various real time applications. In the research for better RS's, especially in the …

The rapid growth of location‐based services (LBSs) has greatly enriched people's urban
lives and attracted millions of users in recent years. Location‐based social networks …

E-commerce platforms are committed to planning various marketing campaigns to make
profits, and the impact of marketing campaigns is determined by the number of consumers …

In this paper, we study the location aware influence maximization problem, which finds a
seed set to maximize the influence spread on targeted users for a given query. In particular …

Traditional recommendation methods based on matrix factorization techniques have yielded
immense success because of their good scalability. However, they still face the problem of …

In this paper, we focus on the problem of discovering internally connected communities in
event-based social networks (EBSNs) and propose a community detection method by …

Online Social networks have become an easy means of communication for users to share
their opinion on various topics, including breaking news, public events, and products. The …

Collaborative filtering techniques are a common approach for building recommendations,
and have been widely applied in real recommender systems. However, collaborative …