Discovery of inference rules for question-answering
Natural Language Engineering
Extracting paraphrases from a parallel corpus
ACL '01 Proceedings of the 39th 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
Paraphrasing with bilingual parallel corpora
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Syntactic constraints on paraphrases extracted from parallel corpora
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning by reading: a prototype system, performance baseline and lessons learned
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Extracting paraphrase patterns from bilingual parallel corpora
Natural Language Engineering
Hitting the right paraphrases in good time
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
A survey of paraphrasing and textual entailment methods
Journal of Artificial Intelligence Research
Generating phrasal and sentential paraphrases: A survey of data-driven methods
Computational Linguistics
Aligning needles in a haystack: paraphrase acquisition across the web
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Mavuno: a scalable and effective Hadoop-based paraphrase acquisition system
Proceedings of the Third Workshop on Large Scale Data Mining: Theory and Applications
Diversity-aware evaluation for paraphrase patterns
TIWTE '11 Proceedings of the TextInfer 2011 Workshop on Textual Entailment
Power-law distributions for paraphrases extracted from bilingual corpora
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Validation of sub-sentential paraphrases acquired from parallel monolingual corpora
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Joint learning of a dual SMT system for paraphrase generation
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Generalizing sub-sentential paraphrase acquisition across original signal type of text pairs
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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Paraphrase generation is an important task that has received a great deal of interest recently. Proposed data-driven solutions to the problem have ranged from simple approaches that make minimal use of NLP tools to more complex approaches that rely on numerous language-dependent resources. Despite all of the attention, there have been very few direct empirical evaluations comparing the merits of the different approaches. This paper empirically examines the tradeoffs between simple and sophisticated paraphrase harvesting approaches to help shed light on their strengths and weaknesses. Our evaluation reveals that very simple approaches fare surprisingly well and have a number of distinct advantages, including strong precision, good coverage, and low redundancy.