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Fuzzy Collaborative Forecasting and Clustering pp 59–72Cite as

Collaborative Framework for Fuzzy Co-clustering

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Abstract

Privacy preserving data mining is a fundamental approach for utilizing multiple databases including personal or sensitive information without fear of information leaks. In this chapter, a framework of securely applying fuzzy co-clustering to multiple cooccurrence information, which is stored in multiple organizations, is reviewed with illustrative examples.

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan

    Tin-Chih Toly Chen

  2. Graduate School of Engineering, Osaka Prefecture University, Sakai, Osaka, Japan

    Katsuhiro Honda

Authors
  1. Tin-Chih Toly Chen
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  2. Katsuhiro Honda
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Correspondence to Tin-Chih Toly Chen .

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Chen, TC.T., Honda, K. (2020). Collaborative Framework for Fuzzy Co-clustering. In: Fuzzy Collaborative Forecasting and Clustering. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-22574-2_5

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