CLIQUE COMMUNITIES IN SOCIAL NETWORKS

Luís Cavique, Armando B. Mendes and Jorge M.A. Santos
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Luís Cavique: Universidade Aberta, Portugal
Armando B. Mendes: Universidade Açores, Portugal
Jorge M.A. Santos: Universidade Évora, Portugal

Chapter 20 in Quantitative Modelling in Marketing and Management, 2012, pp 469-490 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThere is a pressing need for new pattern recognition tools and statistical methods to quantify large graphs and predict the behaviour of network systems, due to the large amount of data which can be extracted from the web. In this work a graph mining metric, based on k-clique communities, is used, allowing a better understanding of the network structure. The proposed metric shows that for different graph families correspond different k-clique sequences.

Keywords: Quantitative Modelling; Statistical; Computer; Marketing; Neural Networks; Fuzzy Logic; k-Clique Model; Meta-heuristics (search for similar items in EconPapers)
Date: 2012
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