期刊文献+

社会合作网络中社团结构的搜索算法研究 被引量:1

An Searching Algorithm for Analyzing Community Structure in Complex Networks
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摘要 许多实际的网络都具有一个共同性质,即它们都是由各个社团通过公共节点连接而成网络,因此,网络中社团的数目以及每个节点归属于社团的数目对于研究复杂网络都具有重要的意义。通过分析复杂网络的社团结构和寻找网络社团数目的传统算法,针对传统算法所存在的缺陷,提出了一种搜索社团结构的算法。该算法正确的对网络的社团结构进行了划分,且较好的改进了其运行效率。最后指出了进一步的研究方向。 Many actual networks all have a common character, namely they are all composed by each consortium through the public node connection, therefor, the number of the consortium and the node which belongs to the consortium are more meaningful to study the complex network. This article analyzes the structure of consortium of complex network and the tradition arithmetic of searching the number of the network consortium, in allusion to the objection of the traditional arithmetic, we also bring up a arithmetic which is searching for consortium construction on the basic of the grade clustering arithmetic. This arithmetic plots the consortium construction of the network correctly, and also improve its function efficiency well. Finally, some future directions are pointed.
出处 《信息技术与信息化》 2008年第2期13-15,共3页 Information Technology and Informatization
关键词 合作网络 社团结构 搜索算法 Collaboration network Community structure Searching algorithm
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参考文献6

  • 1Watts D J, Strogatz S H. Collective dynamics of' small world' networks [ J ]. Nature. 1998,393:440 - 442.
  • 2Barabasi A L , Albert R.. Emergence of scaling in random networks [ J ]. Science, 1999,286:509 - 512.
  • 3Barabasi A L , Albert R. Jeong H, Mean -field theory for scalefree random networks [ J ]. Phys A, 1999,272 : 173 - 187.
  • 4解(亻刍),汪小帆.复杂网络中的社团结构分析算法研究综述[J].复杂系统与复杂性科学,2005,2(3):1-12. 被引量:86
  • 5刘军.社会网分析导论.北京:社会科学文献[M],2004.
  • 6Wasserman S. and Faust K. , Social Network Analysis : Methods and Applications [ M ]. Cambridge University Press, Cambridge 1994.

二级参考文献33

  • 1[1]Gibson D,Kleinberg J,Raghavan P.Inferring web communities from link topology[A].Proceedings of the 9th ACM Conference on Hypertext and Hypermedia[C].1998.225-234.
  • 2[2]Flake G W,Lawrence S R,Giles C L,et al.Self-organization and identification of web communities[J].IEEE Computer,2002,35 (3):66-71.
  • 3[3]Adamic A L,Adar E.Friends and neighbors on the web[J].Social Networks,2003,25 (3):211-130.
  • 4[4]Shen-Orr S,Milo R,Mangan S,et al.Network motifs in the transcriptional regulation network of Escherichia coli[J].Nature Genetics,2002,31 (1):64-68.
  • 5[5]Milo R,Shen-Orr S,Itzkovitz S,et al.Network motifs:simple building blocks of complex networks[J].Science,2002,298 (5594):824-827.
  • 6[6]Holme P,Huss M,Jeong H.Subnetwork hierarchies of biochemical pathways[J].Bioinformatics,2003,19 (4):532-538.
  • 7[7]Girvan M,Newman M E J.Community structure in social and biological networks[J].Proc Natl Acad Sci,2001,99 (12):7 821-7 826.
  • 8[8]Gleiser P,Danon L.Community structure in jazz[J].Advances in Complex Systems,2003,6 (4):565-573.
  • 9[9]Garey M R,Johnson D S.Computers and Intractability:A Guide to the Theory of NP-Completeness[M].San Francisco:W.H.Freeman Publishers,1979.
  • 10[10]Scott J.Social Network Analysis:A Handbook[M].2nd ed.London:Sage Publications,2002.

共引文献85

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  • 1Fortunato S, CasteUano C. Community structure in graphs [ J/ OL]. Eprint arXiv, 2007,0712 : 2716. [ 2009 - 03 - 10 ], http ://ww. arXiv. org.
  • 2Grivan M, Newman M E J. Community structure in social and biological networks[J]. Proc. Natl. Acad. Sci,2001,99:7821 -7826.
  • 3Gleiser P, Danon L. Community structure in jazz[ J ]. Advances in Complex Systems,2003,6:565-573.
  • 4范明,孟小峰.数据挖掘概念与技术[M].第2版.北京:机械工业出版社,2007:85-100.
  • 5Kuncheva L I, Hadjitodorov S T. Using diversity in cluster ensembles[ C]//2004 IEEE International Conference Systems, Mqn and Cybernetics. [ s. l. ] : [ s. n. ] ,2004 : 1212-1219.
  • 6Zhang P, L iM H, Wu J S, et al. The analysis and dissimilarity comparison of community structure[J]. Physica A, 2006, 367 : 577-585.
  • 7陈海强,程学旗,刘悦.基于用户兴趣的寻找虚拟社区核心成员的方法[J].中文信息学报,2009,23(2):89-94. 被引量:14
  • 8荣波,夏正友.基于聚类的BBS成员交互网络特性研究[J].重庆科技学院学报(自然科学版),2009,11(6):165-169. 被引量:5
  • 9荣波,夏正友,朱永真,卜湛.BBS在线复杂网络及其成员交互特性研究[J].复杂系统与复杂性科学,2009,6(4):57-65. 被引量:13
  • 10王爱平,王占凤,陶嗣干,燕飞飞.数据挖掘中常用关联规则挖掘算法[J].计算机技术与发展,2010,20(4):105-108. 被引量:69

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