Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

Link prediction methods anticipate the likelihood of a future connection between two nodes
in a given network. The methods are essential in social networks to infer social interactions …

Abstract eLearning has completely transformed the way in which learning is imparted to
students. Relevance of the topic being taught is often found lacking in learning material …

High-dimensional and sparse (HiDS) matrices are frequently adopted to describe the
complex relationships in various big data-related systems and applications. A Position …

High-dimensional features are extensively accessible in machine learning and computer
vision areas. How to learn an efficient feature representation for specific learning tasks is …

Link prediction aims to predict the missing interactions in evolving networks that may appear
in the future. It has practical importance in various real-world applications, ranging from …

Link prediction is one of the core problems in social network analysis. Considering the
complexity of features in social networks, we propose a link prediction method based on …

Link prediction in complex networks has attracted considerable attention from
interdisciplinary research communities, due to its ubiquitous applications in biological …

Circle structure of online brand communities allows companies to conduct cross-marketing
activities by the influence of friends in different circles and build strong and lasting …

Modeling and predicting social interactions within shared physical spaces is key to
understanding human spatio-temporal behavior. Such models are essential for optimizing …