Coupled Clustering: a Method for Detecting Structural Correspondence

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This paper proposes a new paradigm and computational framework for identification of correspondences between sub-structures of distinct composite systems. For this, we define and investigate a variant of traditional data clustering, termed coupled clustering, which simultaneously identifies corresponding clusters within two data sets. The presented method is demonstrated and evaluated for detecting topical correspondences in textual corpora.
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Machine Learning, Computation and Language, Information Retrieval, H.3.3; I.2.6; I.2.7; I.5.3; I.5.4

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http://salesiana.dossiersoluciones.com/handle/123456789/30702

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cs/0107032
 http://arxiv.org/abs/cs/0107032
 In: C. E. Brodley and A. P. Danyluk (eds.), Proceedings of the 18th International Conference on Machine Learning (ICML 2001), pp. 353-360

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