CLIQUE COMMUNITIES IN SOCIAL NETWORKS

• Author(s): Santos, Jorge ; Cavique, Luís ; Mendes, Armando
• Date: 2012
• Persistent ID: http://hdl.handle.net/10174/7676
• Origin: Repositório Científico da Universidade de Évora
• Subject(s): Data mining; social networks; graph mining
• Document Type: Part of book or chapter of book
• Language: Portuguese
• Editor(s): Kun-Huang, Huarng; Moutinho, Luiz

Description

There 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.