Recent development in the area of social networks has sought attention of the researchers
to crunch and analyse the data and information of the users to retrieve relevant knowledge …

Complex networks are ubiquitous to several computer science domains. Centrality
measures are an important analysis mechanism to uncover vital elements of complex …

Pre-training on graph neural networks (GNNs) aims to learn transferable knowledge for
downstream tasks with unlabeled data, and it has recently become an active research area …

Conventional resource management systems use a system model to describe resources
and a centralized scheduler to control their allocation. We argue that this paradigm does not …

The goal of this tutorial is to expose participants to the current research on social
recommender systems (ie, recommender systems for the social web). Participants will …

Social network analysis (SNA) has attracted a lot of attention in several domains in the past
decades. It can be of 2‐folds: one is content‐based, and another one is structured‐based …

Real-world networks feature weights of interactions, where link weights often represent
some physical attributes. In many situations, to recover the missing data or predict the …

Owing to the self-improvement desire, the human being always tries to reach to the current
information and generate new ones from the data on hand. The practices are realized by …

Link prediction is an important task in data mining, which has widespread applications in
social network research. Given a social network, the objective of this task is to predict future …

Described embodiments include a system that includes a monitoring agent, configured to
automatically monitor usage of a computing device by a user, and a processor. The …