Abstract
Most of clustering methods assume that each object must be assigned to exactly one cluster, however, overlapping clustering is more appropriate than crisp clustering in a variety of important applications such as the network structure analysis and biological information. This paper provides a three-way decision strategy for overlapping clustering based on the decision-theoretic rough set model. Here, each cluster is described by an interval set that is defined by a pair of sets called the lower and upper bounds. Besides, a density-based clustering algorithm is proposed using the new strategy, and the results of the experiments show the strategy is effective to overlapping clustering.
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Yu, H., Wang, Y. (2012). Three-Way Decisions Method for Overlapping Clustering. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_33
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DOI: https://doi.org/10.1007/978-3-642-32115-3_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32114-6
Online ISBN: 978-3-642-32115-3
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