CoMRing: A framework for Community detection based on Multi-Relational querying exploration

Community detection in multi-relational bibliographic networks is an important issue. There has been a surge of interest in community detection focusing on analyzing the linkage or topological structure of these networks. However, communities identified by these proposed approaches, commonly reflect the strength of connections between networks nodes and neglect considering the interesting topics or the venues, i.e., conferences or journals, shared by these community members, i.e, authors. To tackle this drawback, we present in this paper a new approach called CoMRing for community detection from heterogeneous multi-relational network which incorporate the multiple types of objects and relationships, derived from a bibliographic networks. We firstly propose to construct the Concept Lattice Family (CLF) to model the different objects and relations in the multi-relational bibliographic networks using the Relational Concept Analysis (RCA) methods. Then after we introduce a new method, called Query(Exploration), that explores such CLF for community detection. Carried out experiments on real-datasets enhance the effectiveness of our proposal and open promising issues. (C) 2016 The Authors. Published by Elsevier B.V.