Abstract
In this paper, we introduce a community detection approach from heterogeneous multi-relational network which incorporate the multiple types of objects and relationships, derived from a bibliographic networks. The proposed approach performs firstly by constructing the relation context family (RCF) to represent the different objects and relations in the multi-relational bibliographic networks using the Relational Concept Analysis (RCA) methods; and secondly by exploring such RCF for community detection. Experiments performed on a dataset of academic publications from the Computer Science domain enhance the effectiveness of our proposal and open promising issues.
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Acknowledgements
This work is partially supported by the French-Tunisian project PHC-Utique RIMS-FD 14G 1404.
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Guesmi, S., Trabelsi, C., Latiri, C. (2016). Community Detection in Multi-relational Bibliographic Networks. In: Hartmann, S., Ma, H. (eds) Database and Expert Systems Applications. DEXA 2016. Lecture Notes in Computer Science(), vol 9828. Springer, Cham. https://doi.org/10.1007/978-3-319-44406-2_2
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DOI: https://doi.org/10.1007/978-3-319-44406-2_2
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