Community Detection in Bibsonomy Using Data Clustering

@inproceedings{Saoud2017CommunityDI,
  title={Community Detection in Bibsonomy Using Data Clustering},
  author={Zakaria Saoud and Jan Platos},
  booktitle={ISAT},
  year={2017}
}
Community detection aims to extract the related groups of nodes from complex networks, by exploiting the network topology. Different approaches have been proposed for community detection, where most of them are based on clustering algorithms. In this paper we investigate how we can use the clustering for the community detection in the academic social bookmarking website: Bibsonomy. Our goal is to determine the most suitable clustering algorithm for similar user detection in Bibsonomy. To… CONTINUE READING

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