Identifying Social Communities by Frequent Pattern Mining

被引：10

作者：

Adnan, Muhaimenul ^{[1
]}

Alhajj, Reda ^{[1
]}

Rokne, Jon ^{[1
]}

机构：

[1] Univ Calgary, Dept Comp Sci, Calgary, AB T2N 1N4, Canada

来源：

INFORMATION VISUALIZATION, IV 2009, PROCEEDINGS | 2009年

关键词：

NETWORKS;

D O I：

10.1109/IV.2009.49

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a social network modeling technique that models the data to be analyzed to create a social network as frequent closed patterns. Frequent closed patterns have the advantage that they successfully grab the inherent information, content of the dataset and is applicable to a broader application domain. Entropies of the frequent closed patterns are used to keep the dimensionality of the feature vectors to a reasonable size. Experimental results presented in the paper shows that social network produced from these set of features successfully carries the community structure information.

引用

页码：413 / 418

页数：6

共 23 条

[1] Agrawal R., 1993, SIGMOD Record, V22, P207, DOI 10.1145/170036.170072
[2] [Anonymous], P 2 INT C KNOWL DISC
[3] [Anonymous], 1970, Bell System Technical Journal, DOI [10.1002/j.1538-7305.1970.tb01770.x, DOI 10.1002/J.1538-7305.1970.TB01770.X]
[4] BEIL F, 2002, P ACM INT C KNOWL DI
[5] Self-organization and identification of web communities
Flake, GW
Lawrence, S
Giles, CL
Coetzee, FM
[J]. COMPUTER, 2002, 35 (03) : 66 - +
[6] Garofalakis MN, 1999, PROCEEDINGS OF THE TWENTY-FIFTH INTERNATIONAL CONFERENCE ON VERY LARGE DATA BASES, P223
[7] Community structure in social and biological networks
Girvan, M
Newman, MEJ
[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2002, 99 (12) : 7821 - 7826
[8] GRAHNE G, 2003, P ICDM WORKSH FREQ I
[9] Han Jiawei., 2000, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, P355
[10] *JUNG, JAV UN NETW GRAPH FR

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