Cohesive subgraph mining on social networks
Fan Zhang · OPUS - Open Publications of UTS Scholars (University of Technology Sydney) · 2017
Graphs are widely used to represent the abundant information in social networks for discovering promising communities, reinforcing network stability, and finding critical users, to name a few.Cohesive subgraph mining, as one of the most fundamental problems in graphs, gains increasing popularity in social network study for its effectiveness.In this thesis, some basic social components are considered in cohesive subgraphs to better accommodate various real-life applications.Firstly, we investigate the problem of (k,r)-core which intends to find cohesive subgraphs on social networks considering both user engagement and similarity.Efficient algorithms are proposed to enumerate all maximal (k,r)-cores and find