%0 Journal Article
%T Maximal Clique Percolation Algorithm Based on Neighboring Information<br>一种基于邻居信息的最大派系过滤算法
%A CHEN Duan-bing
%A ZHOU Yu-lin
%A FU Yan
%A <br>陈端兵
%A 周玉林
%A 傅彦
%J 计算机科学
%D 2011
%I 
%X Maximal clique problem(MCP) is a classical and important combinational optimization problem with many prominent applications, for example, information retrieval, signal transmission, computer vision, social network and bioinformatics, etc. Researchers presented many algorithms to solve it by using various strategics, such as branch-and-bound, genetic algorithm, simulation annealing, cross entropy and DNA method. In this paper, a new clique percolation algorithm was presented based on neighboring vertices and edges of clique. From a given clique( it's a vertex at initial) at each step, investigated its all neighboring vertices and expanded it to a larger clique through a neighboring edge of clique. Two large scale author collaboration networks were used to test the performance of proposed algorithm and the clique distribution in large scale social network was also discussed. Experimental results demonstrate that the presented algorithm is efficient to percolation the maximal clique in network.
%K Maximal clique problem
%K Social network
%K Clique percolation
%K Neighboring vertex
%K Neighboring edge<br>最大派系问题，社会网络，派系过滤算法，部接顶点，部接边
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=5C1483521471C18500F3EAC2CEB9EBAC&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=CA4FD0336C81A37A&sid=38685BC770C663F2&eid=9F6DA927E843CD50&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=20