DB2SNA : an All-in-one Tool for Extraction and Aggregation of underlying Social Networks from Relational Databases

Abstract : In the enterprise context, People need to visualize different types of interactions between heterogeneous objects (e.g. product and site, customers and product, people interaction (social network)...). The existing approaches focus on social networks extraction using web doc- ument. However a considerable amount of information is stored in relational databases. Therefore, relational databases can be seen as rich sources for extracting a social network. The extracted network has in general a huge size which makes it difficult to analyze and visualize. An aggregation step is needed in order to have more understandable graphs. In this chapter, we propose a heterogeneous object graph extraction approach from a relational database and we present its application to extract social network. This step is followed by an aggregation step in order to improve the visualisation and the analyse of the extracted social network. Then, we aggregate the resulting network using the k-SNAP algorithm which produces a summarized graph.
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Chapitre d'ouvrage
The influence of technology on social network analysis and Mining, Springer, pp.521-546, 2013, 978-3-7091-1345-5
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Contributeur : Marie-Aude Aufaure <>
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Rania Soussi, Etienne Cuvelier, Marie-Aude Aufaure, Amine Louati, Yves Lechevallier. DB2SNA : an All-in-one Tool for Extraction and Aggregation of underlying Social Networks from Relational Databases. The influence of technology on social network analysis and Mining, Springer, pp.521-546, 2013, 978-3-7091-1345-5. 〈hal-00830599〉

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