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
Paraphrasing with bilingual parallel corpora
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Improved statistical machine translation using paraphrases
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Combining online and offline knowledge in UCT
Proceedings of the 24th international conference on Machine learning
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Bandit based monte-carlo planning
ECML'06 Proceedings of the 17th European conference on Machine Learning
A corpus-based method for extracting paraphrases of emotion terms
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
A survey of paraphrasing and textual entailment methods
Journal of Artificial Intelligence Research
The true score of statistical paraphrase generation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Monte-Carlo tree search and rapid action value estimation in computer Go
Artificial Intelligence
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Distributional phrasal paraphrase generation for statistical machine translation
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
Paraphrase acquisition via crowdsourcing and machine learning
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
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We propose a new specifically designed method for paraphrase generation based on Monte-Carlo sampling and show how this algorithm is suitable for its task. Moreover, the basic algorithm presented here leaves a lot of opportunities for future improvement. In particular, our algorithm does not constraint the scoring function in opposite to Viterbi based decoders. It is now possible to use some global features in paraphrase scoring functions. This algorithm opens new outlooks for paraphrase generation and other natural language processing applications like statistical machine translation.