Anzeige
Erschienen in:
2012 | OriginalPaper | Buchkapitel
Graph Mining and Communities Detection
verfasst von : Etienne Cuvelier, Marie-Aude Aufaure
Erschienen in: Business Intelligence
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The incredible rising of on-line social networks gives a new and very strong interest to the set of techniques developed since several decades to mining graphs and social networks. In particular, community detection methods can bring very valuable informations about the structure of an existing social network in the Business Intelligence framework. In this chapter we give a large view, firstly of what could be a community in a social network, and then we list the most popular techniques to detect such communities. Some of these techniques were particularly developed in the SNA context, while other are adaptations of classical clustering techniques. We have sorted them in following an increasing complexity order, because with very big graphs the complexity can be decisive for the choice of an algorithm.