Coupled Clustering: a Method for Detecting Structural Correspondence
<|reference_start|>Coupled Clustering: a Method for Detecting Structural Correspondence: 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.<|reference_end|>
@article{marx2001coupled,
    title={Coupled Clustering: a Method for Detecting Structural Correspondence},
    author={Zvika Marx, Ido Dagan, Joachim Buhmann},
    journal={In: C. E. Brodley and A. P. Danyluk (eds.), Proceedings of the
  18th International Conference on Machine Learning (ICML 2001), pp. 353-360},
    year={2001},
    archivePrefix={arXiv},
    eprint={cs/0107032},
    primaryClass={cs.LG cs.CL cs.IR}
}