Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
On the MSE robustness of batching estimators
Proceedings of the 33nd conference on Winter simulation
Extracting paraphrases from a parallel corpus
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
WWSM '00 Proceedings of the ACL-2000 workshop on Word senses and multi-linguality - Volume 8
Exploiting paraphrases in a Question Answering system
PARAPHRASE '03 Proceedings of the second international workshop on Paraphrasing - Volume 16
Interrogative reformulation patterns and acquisition of question paraphrases
PARAPHRASE '03 Proceedings of the second international workshop on Paraphrasing - Volume 16
Learning trees and rules with set-valued features
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
ParaMT: A Paraphraser for Machine Translation
PROPOR '08 Proceedings of the 8th international conference on Computational Processing of the Portuguese Language
Constructing corpora for the development and evaluation of paraphrase systems
Computational Linguistics
Application-driven statistical paraphrase generation
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
PEM: a paraphrase evaluation metric exploiting parallel texts
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Paraphrasing with search engine query logs
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Leveraging multiple MT engines for paraphrase generation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
A survey of paraphrasing and textual entailment methods
Journal of Artificial Intelligence Research
A generate and rank approach to sentence paraphrasing
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Exploiting discourse information to identify paraphrases
Expert Systems with Applications: An International Journal
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State-of-the-art Question Answering (QA) systems are very sensitive to variations in the phrasing of an information need. Finding the preferred language for such a need is a valuable task. We investigate that claim by adopting a simple MT-based paraphrasing technique and evaluating QA system performance on paraphrased questions. We found a potential increase of 35% in MRR with respect to the original question.