Learning cross-document structural relationships using boosting
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Extracting paraphrases from a parallel corpus
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Learning to paraphrase: an unsupervised approach using multiple-sequence alignment
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Syntax-based alignment of multiple translations: extracting paraphrases and generating new sentences
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Paraphrase acquisition for information extraction
PARAPHRASE '03 Proceedings of the second international workshop on Paraphrasing - Volume 16
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Paraphrases and other semantically related sentences present a challenge to NLP and IR applications such as multi-document summarization and question answering systems. While it is generally agreed that paraphrases contain approximately equivalent ideas, they often differ from one another in subtle, yet non-trivial, ways. In this paper, we examine semantic differences in cases of paraphrase and subsumption, in an effort to understand what makes one sentence significantly more informative than another. Using manually annotated data from the news domain, we concentrate on developing a framework for analyzing and comparing pairs of related sentences.