Automatic Threshold Calculation Based Label Propagation Algorithm for Overlapping Community

2016 ◽  
Author(s):  
Gongshen Liu ◽  
Kui Meng ◽  
Hongyi Guo ◽  
Li Pan ◽  
Jianhua Li
Keyword(s):  
Label Propagation ◽  
Propagation Algorithm ◽  
Overlapping Community

scholarly journals Adaptive Label Propagation Algorithm to Detect Overlapping Community in Complex Networks

2016 ◽  
Vol 9 (8) ◽  
pp. 317-326 ◽  
Author(s):  
Chunying Li ◽  
Yonghang Huang ◽  
Zhikang Tang ◽  
Yong Tang ◽  
Jiandong Zhao
Keyword(s):  
Complex Networks ◽  
Label Propagation ◽  
Propagation Algorithm ◽  
Overlapping Community

Node Importance based Label Propagation Algorithm for overlapping community detection in networks

2020 ◽  
Vol 162 ◽  
pp. 113020 ◽  
Author(s):  
Imen Ben El Kouni ◽  
Wafa Karoui ◽  
Lotfi Ben Romdhane
Keyword(s):  
Community Detection ◽  
Label Propagation ◽  
Overlapping Community Detection ◽  
Node Importance ◽  
Propagation Algorithm ◽  
Overlapping Community

Parallel Multi-Label Propagation Based on Influence Model and Its Application to Overlapping Community Discovery

2017 ◽  
Vol 26 (03) ◽  
pp. 1760013 ◽  
Author(s):  
Qirong Qiu ◽  
Wenzhong Guo ◽  
Yuzhong Chen ◽  
Kun Guo ◽  
Rongrong Li
Keyword(s):  
Complex Network ◽  
Label Propagation ◽  
Community Discovery ◽  
Influence Model ◽  
Propagation Algorithm ◽  
Overlapping Community ◽  
High Scalability ◽  
Computationally Intensive ◽  
Mapreduce Model ◽  
Intensive Work

Finding communities in networks is one of the challenging issues in complex network research. We have to deal with very large networks that contain billions of vertices, which makes community discovery a computationally intensive work. Moreover, communities usually overlap each other, which greatly increases the difficulty of identifying the boundaries of communities. In this paper, we propose a parallel multi-label propagation algorithm (PMLPA) that enhances traditional multi-label propagation algorithm (MLPA) in two ways. First, the critical steps of MLPA are parallelized based on the MapReduce model to get higher scalability. Second, new label updating strategy is used to automatically determine the most valuable labels of each vertex. Furthermore, we study the improvement of PMLPA through considering the influence of vertices and labels on label updating. In this way, the importance of each label can be described with higher precision. Experiments on artificial and real networks prove that the proposed algorithms can achieve both high discovering accuracy and high scalability.

LinkLPA: A Link-Based Label Propagation Algorithm for Overlapping Community Detection in Networks

2016 ◽  
Vol 33 (2) ◽  
pp. 308-331 ◽  
Author(s):  
Heli Sun ◽  
Jiao Liu ◽  
Jianbin Huang ◽  
Guangtao Wang ◽  
Xiaolin Jia ◽  
...  
Keyword(s):  
Community Detection ◽  
Label Propagation ◽  
Overlapping Community Detection ◽  
Propagation Algorithm ◽  
Overlapping Community

LPX: Overlapping community detection based on X‐means and label propagation algorithm in attributed networks

2020 ◽  
Author(s):  
Jinhuan Ge ◽  
Heli Sun ◽  
Chenhao Xue ◽  
Liang He ◽  
Xiaolin Jia ◽  
...  
Keyword(s):  
Community Detection ◽  
Label Propagation ◽  
Overlapping Community Detection ◽  
Propagation Algorithm ◽  
Overlapping Community ◽  
Attributed Networks
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