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| LFM Community Detection Algorithm Based on Vertex Similarity |
| YANG Xiaobo1, CHEN Chuxiang1, WANG Zhiwan2
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1.College of Science, The Information Engineering University, Zhengzhou 450000, China;
2.Respiratory Department, the First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou 450000, China |
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Abstract In network with fuzzy community structure, precision of the traditional LFM algorithm decreases apparently. In order to solve this problem, an LFMJ algorithm is presented. Using the information of neighbor nodes and improved Jaccard coefficient, this algorithm reconstructed the network structure, and improved the precision of community division results. To validate the algorithm, five algorithms was tested in LFR benchmark and real networks, including LFMJ, traditional LFM, LPA algorithm and WT, FUA algorithm, which have better performance in community detection. The results show that, in LFR network, the accuracy of LFMJ is higher than both LFM and LPA, equaling to WT and FUA algorithm. In real network and LFR network with overlapping community, LFMJ gets the highest accuracy than others. The effectiveness of the algorithm is proved.
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Received: 08 November 2016
Published: 10 January 2019
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