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Community Detection in Knowledge Graph Network with Matrix Factorization Learning

  • Xiaohua ShiEmail author
  • Yin Qian
  • Hongtao Lu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11809)

Abstract

Recently, knowledge graph is one of most hot topics in artificial intelligence research area, we may find that data in knowledge graph analysis shows vast network structure features. In this paper, we investigate some main methods of current network analysis and community detection tasks related with knowledge graph and semantic network. Comparing with relevant network community detection methods in various semantic network data, our matrix factorization learning method achieves good performance for community detection.

Keywords

Knowledge graph Semantic network Network analysis Community detection Matrix factorization learning 

Notes

Acknowledgments

This work was supported by NSFC (Grant No. 61772330), China Next Generation Internet IPv6 project (Grant No. NGII20170609), and the Social Science Planning of Shanghai (Grant No. 2018BTQ002).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.LibraryShanghai Jiaotong UniversityShanghaiChina
  2. 2.Department of Computer ScienceShanghai JiaoTong UniversityShanghaiChina

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