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Combinational Meta-paths Mining for Correlation Relationship Evaluation in Bibliographic Networks

  • Qinchen Wu
  • Peng Wu
  • Li PanEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 252)

Abstract

Correlation relationships between objects are pervasive in heterogeneous information networks such as bibliographic networks, which made it possible to evaluate proximity between nodes from different perspectives. To explain these semantically rich correlations, meta-paths formed by interconnected node types and edge types have been widely used. This means, using meta-paths and their combinations we can explicitly evaluate relationships between nodes, and thus made it possible to search for proximate nodes according to specific correlations they carried. In this paper, we propose a combinational meta-paths mining algorithm to evaluate correlation relationships between nodes in bibliographic networks. Experiments with bibliographic networks have proved its effectiveness with respect to prior knowledge based results.

Keywords

Heterogeneous information networks Meta-paths Correlation relationships Node-pairs proximity 

Notes

Acknowledgements

This work is supported by National Key Research and Development Plan in China (2017YFB0803300), National Natural Science Foundation of China (U1636105).

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.National Engineering Laboratory for Information Content Analysis Technology, School of Electric Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina

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