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A Probability Transition Matrix-Based Recommendation Algorithm for Bipartite Networks

  • Dongming Chen
  • Chang Liu
  • Xinyu Huang
  • Dongqi WangEmail author
  • Jiarui Yan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)

Abstract

By analyzing the searching and recommendation system in the electronic commerce field, this paper provides a retrieval sorting and recommendation algorithm for e-commerce service. An information transmission matrix is constructed based on the ‘customer-product’ bipartite networks, and the rankings of customers and products can be obtained by analyzing the network structures. Then we propose a community detection algorithm for bipartite networks, by employing the information transmission matrix. Finally, the recommendation scheme based on both customers and products is obtained. It makes recommendation results more comprehensive and reasonable, which satisfies the various requirements of the customers.

Keywords

Bipartite networks Sorting Recommendation Probability transition 

Notes

Acknowledgements

This work is partially supported by Liaoning Natural Science Foundation under Grant No. 20170540320, the Doctoral Scientific Research Foundation of Liaoning Province under Grant No. 20170520358, the Fundamental Research Funds for the Central Universities under Grant No. N161702001, No. N172410005-2.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Dongming Chen
    • 1
  • Chang Liu
    • 1
  • Xinyu Huang
    • 1
  • Dongqi Wang
    • 1
    Email author
  • Jiarui Yan
    • 1
  1. 1.Software CollegeNortheastern UniversityShenyangChina

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