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2009 13th International Conference Information Visualisation
Identifying Social Communities by Frequent Pattern Mining
Barcelona, Spain
July 15-July 17
ISBN: 978-0-7695-3733-7
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.
Index Terms:
social network analysis, frequent pattern mining
Citation:
Muhaimenul Adnan, Reda Alhajj, Jon Rokne, "Identifying Social Communities by Frequent Pattern Mining," iv, pp.413-418, 2009 13th International Conference Information Visualisation, 2009
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