Social Networks Mining Based on Information Retrieval Technologies and Bees Swarm Optimization: Application to DBLP

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 206)

Abstract

Unlike the previous works where detecting communities is performed on large graphs, our approach considers textual documents for discovering potential social networks. More precisely, the aim of this paper is to extract social communities from a collection of documents and a query specifying the domain of interest that may link the group. We propose a methodology which develops an information retrieval system capable to generate the documents that are in relationship with any topic. The authors of these documents are linked together to constitute the social community around the given thematic. The search process in the information retrieval system is designed using a bee swarm optimization method in order to optimize the retrieval time. Our approach was implemented and tested on CACM and DBLP and the time of building a social network is quasi instant.

Keywords

social network knowledge mining information retrieval BSO DBLP 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer ScienceUSTHB, LRIAAlgiersAlgeria

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