Detecting a community in a network is a matter of discerning the distinct features and
connections of a group of members that are different from those in other communities. The …

Community detection, a fundamental task for network analysis, aims to partition a network
into multiple sub-structures to help reveal their latent functions. Community detection has …

As communities represent similar opinions, similar functions, similar purposes, etc.,
community detection is an important and extremely useful tool in both scientific inquiry and …

Background The rapid growth in the complexity of services and stringent quality
requirements present a challenge to all healthcare facilities, especially from an economic …

Graph embedding is an effective yet efficient way to convert graph data into a low
dimensional space. In recent years, deep learning has applied on graph embedding and …

Community partition is of great importance in social networks because of the rapid
increasing network scale, data and applications. We consider the community partition …

Community detection technologies have the general research significance in complex
networks, in which the topology information of network is worthy to be the focus for its widely …

In recent decades, efforts have been made to achieve a positive coexistence among
adolescents in secondary schools and create a healthy environment to prepare them to face …

Abstract In modern Online Social Networks (OSNs), the need to detect users' communities
based on their interests and social connections has became a more and more important …

With the continuous development of technology and networks, real-life interactions are
gradually being abstracted into social networks for study. Social circles are a fundamental …