  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.
