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Reinforcement Label Propagation Algorithm Based on History Record

  • Kai LiuEmail author
  • Yi Zhang
  • Kai Lu
  • Xiaoping Wang
  • Xin Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10638)

Abstract

With the continuous development of Internet, social networks are becoming more and more complex, and the research on these complex networks has attracted many researchers’ attention. A large number of community discovery algorithms have emerged, among which the label propagation algorithm is widely used because of its simplicity and efficiency. However, this algorithm has poor stability due to the randomness in the label propagation process. To solve the problem, we propose a reinforcement label propagation algorithm (RLPA) in this paper. In RLPA, a similarity matrix is generated from the historical records of classification, which can be adopted to obtain the final result of community detection. The experimental results show that our algorithm can not only get better performance in accuracy, but also has higher stability.

Keywords

Data mining Community discovery Label propagation algorithm 

Notes

Acknowledgement

This work is supported by National High-tech R&D Program of China (863 Program) under Grants 2015AA01A301, 2015AA010901, and 2015AA01A301, by program for New Century Excellent Talents in University by National Science Foundation (NSF) China 61272142, 61402492, 61402486, 61379146, 61272483, by the open project of State Key Laboratory of High-end Server & Storage Technology (2014HSSA01).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Kai Liu
    • 1
    Email author
  • Yi Zhang
    • 1
  • Kai Lu
    • 1
  • Xiaoping Wang
    • 1
  • Xin Wang
    • 1
  1. 1.Science and Technology on Parallel and Distributed Processing Laboratory, College of ComputerNational University of Defense TechnologyChangshaPeople’s Republic of China

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