PLinkSHRINK: a parallel overlapping community detection algorithm with Link-Graph for large networks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yunlei Zhang ◽  
Dingyi Yin ◽  
Bin Wu ◽  
Feiyu Long ◽  
Yinchang Cui ◽  
...  
Keyword(s):  
Community Detection ◽  
Detection Algorithm ◽  
Large Networks ◽  
Overlapping Community Detection ◽  
Overlapping Community ◽  
Community Detection Algorithm

scholarly journals Overlapping Community Detection Based on Attribute Augmented Graph

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 680
Author(s):  
Hanyang Lin ◽  
Yongzhao Zhan ◽  
Zizheng Zhao ◽  
Yuzhong Chen ◽  
Chen Dong
Keyword(s):  
Community Detection ◽  
Real World ◽  
Detection Algorithm ◽  
Overlapping Community Detection ◽  
Overlapping Communities ◽  
Adjustment Strategy ◽  
Topology Information ◽  
Overlapping Community ◽  
Real World Datasets ◽  
Community Detection Algorithm

There is a wealth of information in real-world social networks. In addition to the topology information, the vertices or edges of a social network often have attributes, with many of the overlapping vertices belonging to several communities simultaneously. It is challenging to fully utilize the additional attribute information to detect overlapping communities. In this paper, we first propose an overlapping community detection algorithm based on an augmented attribute graph. An improved weight adjustment strategy for attributes is embedded in the algorithm to help detect overlapping communities more accurately. Second, we enhance the algorithm to automatically determine the number of communities by a node-density-based fuzzy k-medoids process. Extensive experiments on both synthetic and real-world datasets demonstrate that the proposed algorithms can effectively detect overlapping communities with fewer parameters compared to the baseline methods.

Erratum: An overlapping community detection algorithm based on node distance of line graph

2019 ◽  
Vol 33 (30) ◽  
pp. 1992001
Author(s):  
Guishen Wang ◽  
Yuanwei Wang ◽  
Kaitai Wang ◽  
Zhihua Liu ◽  
Lijuan Zhang ◽  
...  
Keyword(s):  
Community Detection ◽  
Line Graph ◽  
Detection Algorithm ◽  
Overlapping Community Detection ◽  
Overlapping Community ◽  
Community Detection Algorithm

A Novel Overlapping Community Detection Algorithm of Weighted Networks

2014 ◽  
Vol 599-601 ◽  
pp. 1369-1373
Author(s):  
Huang Bin You ◽  
Xue Wu Zhang ◽  
Huai Yong Fu ◽  
Zhuo Zhang ◽  
Min Li ◽  
...  
Keyword(s):  
Community Structure ◽  
Community Detection ◽  
Classification Accuracy ◽  
Time Complexity ◽  
Maximum Degree ◽  
Detection Algorithm ◽  
Overlapping Community Detection ◽  
Weighted Networks ◽  
Overlapping Community ◽  
Community Detection Algorithm

The community structure is a vital property of complex networks. As special networks the weighted networks also have community structure. Nowadays the studies of overlapping community draw attentions of researchers. However, the scale of networks become huge, so it requires the algorithm has lower time complexity and higher classification accuracy. Many existing algorithms cannot meet these two requirements at the same time. So we propose a novel overlapping community detection algorithm. Firstly we apply maximum degree node and its some special adjacent nodes as the initial community, and then expand the initial community by adding eligible nodes to it, finally other communities can be found by repeating these two steps. Experiments results show that our algorithm can detect overlapping community structure from weighted networks successfully, and also reveal that our method has higher division accuracy and lower time complexity than many previously proposed methods.

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