Coupled Clustering: a Method for Detecting Structural Correspondence

2001/07/23 by Zvika Marx, Ido Dagan, Joachim Buhmann
Computer Science · #cs.LG #cs.CL #cs.IR

paper · pdf

published as In: C. E. Brodley and A. P. Danyluk (eds.), Proceedings of the 18th International Conference on Machine Learning (ICML 2001), pp. 353-360 · html with 5 figures

arxiv created 2001/07/23 · arxiv updated 2009/11/30

Abstract

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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