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September 10, 2025IEEE Transactions on Fuzzy Systems

Scalable Fuzzy Clustering With Collaborative Structure Learning and Preservation

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Authors

BJBingbing JiangCZChenglong ZhangZWZhongli Wang

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Overview

Proposed method enhances clustering effectiveness and scalability by integrating membership degrees and similarity structures.

Key Points

  • CSLP improves clustering labels by fully utilizing similarity structures during the process, enhancing performance.
  • Key evidence shows that CSLP outperforms traditional fuzzy clustering methods in both effectiveness and computational efficiency.
  • The method employs iterative strategies to solve the optimization challenge, making it suitable for large-scale datasets.
  • By updating graphs in sync with data similarities, CSLP achieves better collaborative learning of cluster structures.

Cite This Study

Jiang et al. (2025) studied this question.

synapsesocial.com/papers/68c189ca9b7b07f3a0612ec7https://doi.org/10.1109/tfuzz.2025.3581679
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