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Privacy Preserving Collaborative Fuzzy Co-clustering of Three-Mode Cooccurrence Data

  • Katsuhiro Honda
  • Shotaro Matsuzaki
  • Seiki Ubukata
  • Akira Notsu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11144)

Abstract

Co-cluster structure analysis with three-mode cooccurrence information is a potential approach in summarizing multi-source relational data in such tasks as user-product purchase history analysis. This paper proposes a privacy preserving framework for jointly performing three-mode fuzzy co-clustering under collaboration among two organizations, which independently store object-item cooccurrence information and item-ingredient cooccurrence information, respectively. Even when they cannot mutually share elements of the cooccurrence matrices, the intrinsic co-cluster structures are revealed without publishing each elements of relational data but sharing only the structural information.

Keywords

Fuzzy-clustering Co-clustering Three-mode cooccurrence information Privacy preserving data analysis 

Notes

Acknowledgment

This work was supported in part by Tateisi Science and Technology Foundation through 2017 research grant (A).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Katsuhiro Honda
    • 1
  • Shotaro Matsuzaki
    • 1
  • Seiki Ubukata
    • 1
  • Akira Notsu
    • 1
  1. 1.Osaka Prefecture UniversitySakaiJapan

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