Algorithms for Clustering Terms in Document Set Based on Fuzzy Neighborhoods

@article{Miyamoto2005AlgorithmsFC,
  title={Algorithms for Clustering Terms in Document Set Based on Fuzzy Neighborhoods},
  author={Sadaaki Miyamoto and Erina Kataoka},
  journal={The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05.},
  year={2005},
  pages={979-984}
}
This paper describes similarity measures between two terms in a document set using the concept of a fuzzy neighborhood and algorithms for term clustering. Theoretical properties of neighborhood and similarity measures are studied. Agglomerative hierarchical as well as fuzzy/crisp c-means clustering algorithms are proposed. Examples of agglomerative and c-means clustering are given 

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