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Large graph mining: recent developments, challenges and potential solutions

With the recent growth of the graph-based data, the large graph processing becomes more and more important. In order to explore and to extract knowledge from such data, graph mining methods, like community detection, is a necessity. The legacy graph processing tools mainly rely on single machine computational capacity, which cannot process large graphs with billions of nodes. Therefore, the main challenge of new tools and frameworks lies on the development of new paradigms that are scalable, efficient and flexible. In this paper, we review the new paradigms of large graph processing and their applications to graph mining domains using the distributed and shared nothing approach used for large data by internet players.

 

Sabri Skhiri, and Salim Jouili, Large Graph Mining: Recent Developments, Challenges and Potential Solutions, presentation during the European Business Intelligence Summer School (eBISS 2012) organized by the Université Libre de Bruxelles and the Ecole Centrale Paris, Brussels, Belgium, July 2012.

Click here to access the paper in its preprint form.

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