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NAACL
2003

Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment

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Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
We address the text-to-text generation problem of sentence-level paraphrasing — a phenomenon distinct from and more difficult than word- or phrase-level paraphrasing. Our approach applies multiple-sequence alignment to sentences gathered from unannotated comparable corpora: it learns a set of paraphrasing patterns represented by word lattice pairs and automatically determines how to apply these patterns to rewrite new sentences. The results of our evaluation experiments show that the system derives accurate paraphrases, outperforming baseline systems.
Regina Barzilay, Lillian Lee
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where NAACL
Authors Regina Barzilay, Lillian Lee
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