Research On Multiple Local Community Detection Algorithm

Community structures exist in networks composed of nodes and edges,and the connections between nodes in the same community are denser.Community detection is to find all communities in the network,however,sometimes what matters is the community of a certain node,and don't need to detect all communities,which called Local Community Detection.Local community detection aims to find the communities of a given seed node.Most existing works on this problem are based on a very strict assumption that the seed node only belongs to a single community,but in real-world networks,nodes are likely to belong to multiple communities.This thesis first introduce a novel algorithm,HqsMLCD,that can detect multiple communities for a given seed node over static networks.HqsMLCD first finds the high-quality seeds which can detect better communities than the given seed node with the help of network representation,then expands the high-quality seeds one-by-one to get multiple communities,probably overlapping.Since dynamic networks also acts an important role in practice,this thesis extend the static HqsMLCD to handle dynamic networks,and introduce HqsDMLCD.HqsDMLCD mainly integrates dynamic network embedding and dynamic local community detection into the static one.Experimental results on real-world networks demonstrate that our new method HqsMLCD outperforms the state-of-the-art multiple local community detection algorithms.And our dynamic method HqsDMLCD gets comparable results with the static method on real-world networks.