CLIQUE COMMUNITIES IN SOCIAL NETWORKS
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, a...
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| Outros Autores: | , |
| Formato: | bookPart |
| Idioma: | por |
| Publicado em: |
2013
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10174/7676 |
| País: | Portugal |
| Oai: | oai:dspace.uevora.pt:10174/7676 |
| Resumo: | 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. |
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