1999/08/01 by Zvika Marx, Ido Dagan, Eli Shamir
Computer Science · #cs.CL
published as Proceedings of ACL'99 Workshop on Unsupervised Learning in Natural Language Processing, 1999, pp 45-51 · html with 3 gif figures; generated from 7 pages MS-Word file
arxiv created 1999/08/01 · arxiv updated 2009/11/30
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.