Coupled Clustering: a Method for Detecting Structural Correspondence
Machine Learning
2007-05-23 v1 Computation and Language
Information Retrieval
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.
Cite
@article{arxiv.cs/0107032,
title = {Coupled Clustering: a Method for Detecting Structural Correspondence},
author = {Zvika Marx and Ido Dagan and Joachim Buhmann},
journal= {arXiv preprint arXiv:cs/0107032},
year = {2007}
}
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