Abstract
This paper addresses a novel task of detecting sub-topic correspondence in a pair of text fragments, enhancing common notions of text similarity. This task is addressed by coupling corresponding term subsets through bipartite clustering. The paper presents a cost-based clustering scheme and compares it with a bipartite version of the single-link method, providing illustrating results.
Original language | American English |
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Title of host publication | 37thAnnual Meeting of the Association for Computational Linguistics (ACL) |
State | Published - 1999 |