Recently, semi-supervised clustering attracts many researchers' interest. In particular, constraint-based semi-supervised clustering is focused and the constraints of must-link and cannot-link play very important role in the clustering. There are many kinds of relations as well as must-link or cannot-link and one of the most typical relations is the trade-off relation. Thus, in this paper we formulate the trade-off relation and propose a new "semi-supervised" concept called mutual relation. Moreover, we construct two types of new clustering algorithms with the mutual relation constraints based on the well-known and useful fuzzy c-means, called fuzzy c-means with the mutual relation constraints. © 2011 Springer-Verlag.
CITATION STYLE
Endo, Y., & Hamasuna, Y. (2011). Fuzzy c-means clustering with mutual relation constraints: Construction of two types of algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6881 LNAI, pp. 131–140). https://doi.org/10.1007/978-3-642-23851-2_14
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