Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …

The process of opinion formation and evolution is an important part of the study of opinion
dynamics. However, the existing opinion dynamics ignore the relationship between opinion …

Graph clustering is a fundamental task which discovers communities or groups in networks.
Recent studies have mostly focused on developing deep learning approaches to learn a …

By averaging over atomic details, coarse-grained (CG) models provide profound
computational and conceptual advantages for studying soft materials. In particular, bottom …

Network embedding assigns nodes in a network to low-dimensional representations and
effectively preserves the network structure. Recently, a significant amount of progresses …

This book is a comprehensive introduction to quantitative approaches to complex adaptive
systems. Practically all areas of life on this planet are constantly confronted with complex …

Background Despite recent advances in the understanding of the swine gut microbiome at
different growth stages, a comprehensive longitudinal study of the lifetime (birth to market) …

The concept of sustainable development has gained worldwide attention in recent years
which had enhanced its implementation. However, few studies have attempted to map the …

Clustering is a fundamental machine learning task which has been widely studied in the
literature. Classic clustering methods follow the assumption that data are represented as …

Social media, such as Twitter and Facebook, plays a critical role in disaster management by
propagating emergency information to a disaster-affected community. It ranks as the fourth …