MATEC Web Conf.
Volume 176, 20182018 6th International Forum on Industrial Design (IFID 2018)
|Number of page(s)||6|
|Section||Information Technology and Cloud Design Service Platform|
|Published online||02 July 2018|
Community Mining Algorithm Based on Structural Similarity
College of Information Science and Engineering, Shandong Agricultural University, Tai'an, China
2 College of Agricultural, Shandong Agricultural University, Tai' an, China
In order to improve the efficiency of community mining algorithm and the accuracy of community classification, a community mining algorithm based on structural similarity is proposed in this paper. The algorithm uses the structural similarity as an edge weight to perform the operation of the loop deletion, and implements community merging for isolated nodes, thus improving the precision of community division. The algorithm is compared with GN and SSNCA algorithm in classic data sets such as Zachary network, football data and dolphin social network. The experimental results show that the algorithm can effectively detect the community structure in complex networks, and the accuracy of classification and operation speed are obviously improved.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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