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Volumn , Issue , 2015, Pages 373-382

Learning to rank short text pairs with convolutional deep neural networks

Author keywords

Convolutional neural networks; Learning to rank; Microblog search; Question answering

Indexed keywords

COMPUTER VISION; CONVOLUTION; INFORMATION RETRIEVAL; NETWORK ARCHITECTURE; NEURAL NETWORKS; QUERY PROCESSING; SEMANTICS; SPEECH RECOGNITION; SYNTACTICS;

EID: 84953775876     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2766462.2767738     Document Type: Conference Paper
Times cited : (757)

References (40)
  • 2
    • 84953766655 scopus 로고    scopus 로고
    • Open question answering with weakly supervised embedding models
    • Nancy, France, September
    • J. W. Antoine Bordes and N. Usunier. Open question answering with weakly supervised embedding models. In ECML, Nancy, France, September 2014.
    • (2014) ECML
    • Antoine Bordes, J.W.1    Usunier, N.2
  • 4
    • 84883081835 scopus 로고    scopus 로고
    • Pseudo test collections for training and tuning microblog rankers
    • R. Berendsen, M. Tsagkias, W. Weerkamp, and M. De Rijke. Pseudo test collections for training and tuning microblog rankers. In SIGIR, 2013.
    • (2013) SIGIR
    • Berendsen, R.1    Tsagkias, M.2    Weerkamp, W.3    De Rijke, M.4
  • 7
    • 36448990556 scopus 로고    scopus 로고
    • Reranking answers from definitional QA using language models
    • Y. Chen, M. Zhou, and S. Wang. Reranking answers from definitional QA using language models. In ACL, 2006.
    • (2006) ACL
    • Chen, Y.1    Zhou, M.2    Wang, S.3
  • 8
    • 56449095373 scopus 로고    scopus 로고
    • A unified architecture for natural language processing: Deep neural networks with multitask learning
    • R. Collobert and J. Weston. A unified architecture for natural language processing: deep neural networks with multitask learning. In ICML, pages 160-167, 2008.
    • (2008) ICML , pp. 160-167
    • Collobert, R.1    Weston, J.2
  • 9
    • 70349242830 scopus 로고    scopus 로고
    • Generic soft pattern models for definitional QA
    • Salvador, Brazil, ACM
    • H. Cui, M. Kan, and T. Chua. Generic soft pattern models for definitional QA. In SIGIR, Salvador, Brazil, 2005. ACM.
    • (2005) SIGIR
    • Cui, H.1    Kan, M.2    Chua, T.3
  • 12
    • 80052250414 scopus 로고    scopus 로고
    • Adaptive subgradient methods for online learning and stochastic optimization
    • J. Duchi, E. Hazan, and Y. Singer. Adaptive subgradient methods for online learning and stochastic optimization. J. Mach. Learn. Res., 12:2121-2159, 2011.
    • (2011) J. Mach. Learn. Res. , vol.12 , pp. 2121-2159
    • Duchi, J.1    Hazan, E.2    Singer, Y.3
  • 13
    • 24344457554 scopus 로고    scopus 로고
    • A noisy-channel approach to question answering
    • A. Echihabi and D. Marcu. A noisy-channel approach to question answering. In ACL, 2003.
    • (2003) ACL
    • Echihabi, A.1    Marcu, D.2
  • 15
    • 80054692769 scopus 로고    scopus 로고
    • Tree edit models for recognizing textual entailments, paraphrases, and answers to questions
    • M. Heilman and N. A. Smith. Tree edit models for recognizing textual entailments, paraphrases, and answers to questions. In NAACL, 2010.
    • (2010) NAACL
    • Heilman, M.1    Smith, N.A.2
  • 17
    • 33745772402 scopus 로고    scopus 로고
    • Finding similar questions in large question and answer archives
    • J. Jeon, W. B. Croft, and J. H. Lee. Finding similar questions in large question and answer archives. In CIKM, 2005.
    • (2005) CIKM
    • Jeon, J.1    Croft, W.B.2    Lee, J.H.3
  • 19
    • 84961376850 scopus 로고    scopus 로고
    • Convolutional neural networks for sentence classification
    • Doha, Qatar, October
    • Y. Kim. Convolutional neural networks for sentence classification. In EMNLP, pages 1746-1751, Doha, Qatar, October 2014.
    • (2014) EMNLP , pp. 1746-1751
    • Kim, Y.1
  • 21
    • 70349231969 scopus 로고    scopus 로고
    • Exploiting syntactic and shallow semantic kernels for question/answer classification
    • A. Moschitti, S. Quarteroni, R. Basili, and S. Manandhar. Exploiting syntactic and shallow semantic kernels for question/answer classification. In ACL, 2007.
    • (2007) ACL
    • Moschitti, A.1    Quarteroni, S.2    Basili, R.3    Manandhar, S.4
  • 25
    • 84859913631 scopus 로고    scopus 로고
    • Question answering as question-biased term extraction: A new approach toward multilingual qa
    • Y. Sasaki. Question answering as question-biased term extraction: A new approach toward multilingual qa. In ACL, 2005.
    • (2005) ACL
    • Sasaki, Y.1
  • 26
    • 84906925685 scopus 로고    scopus 로고
    • Automatic feature engineering for answer selection and extraction
    • Seattle, Washington, USA, October, Association for Computational Linguistics
    • A. Severyn and A. Moschitti. Automatic feature engineering for answer selection and extraction. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pages 458-467, Seattle, Washington, USA, October 2013. Association for Computational Linguistics.
    • (2013) Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing , pp. 458-467
    • Severyn, A.1    Moschitti, A.2
  • 28
    • 79960232116 scopus 로고    scopus 로고
    • Using semantic roles to improve question answering
    • D. Shen and M. Lapata. Using semantic roles to improve question answering. In EMNLP-CoNLL, 2007.
    • (2007) EMNLP-CoNLL
    • Shen, D.1    Lapata, M.2
  • 31
    • 79958717927 scopus 로고    scopus 로고
    • Learning to rank answers to non-factoid questions from web collections
    • June
    • M. Surdeanu, M. Ciaramita, and H. Zaragoza. Learning to rank answers to non-factoid questions from web collections. Comput. Linguist., 37(2):351-383, June 2011.
    • (2011) Comput. Linguist. , vol.37 , Issue.2 , pp. 351-383
    • Surdeanu, M.1    Ciaramita, M.2    Zaragoza, H.3
  • 32
    • 0038081853 scopus 로고    scopus 로고
    • SVM answer selection for open-domain question answering
    • J. Suzuki, Y. Sasaki, and E. Maeda. Svm answer selection for open-domain question answering. In COLING, 2002.
    • (2002) COLING
    • Suzuki, J.1    Sasaki, Y.2    Maeda, E.3
  • 33
    • 84904549928 scopus 로고    scopus 로고
    • Question answering using enhanced lexical semantic models
    • August
    • W. Tau Yih, M.-W. Chang, C. Meek, and A. Pastusiak. Question answering using enhanced lexical semantic models. In ACL, August 2013.
    • (2013) ACL
    • Tau Yih, W.1    Chang, M.-W.2    Meek, C.3    Pastusiak, A.4
  • 34
    • 79551480483 scopus 로고    scopus 로고
    • Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
    • Dec.
    • P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. J. Mach. Learn. Res., 11:3371-3408, Dec. 2010.
    • (2010) J. Mach. Learn. Res. , vol.11 , pp. 3371-3408
    • Vincent, P.1    Larochelle, H.2    Lajoie, I.3    Bengio, Y.4    Manzagol, P.-A.5
  • 35
    • 80053434997 scopus 로고    scopus 로고
    • Probabilistic tree-edit models with structured latent variables for textual entailment and question answering
    • M. Wang and C. D. Manning. Probabilistic tree-edit models with structured latent variables for textual entailment and question answering. In ACL, 2010.
    • (2010) ACL
    • Wang, M.1    Manning, C.D.2
  • 36
    • 80053356836 scopus 로고    scopus 로고
    • What is the jeopardy model? A quasi-synchronous grammar for qa
    • M. Wang, N. A. Smith, and T. Mitaura. What is the jeopardy model? a quasi-synchronous grammar for qa. In EMNLP, 2007.
    • (2007) EMNLP
    • Wang, M.1    Smith, N.A.2    Mitaura, T.3
  • 37
    • 84916213998 scopus 로고    scopus 로고
    • Answer extraction as sequence tagging with tree edit distance
    • P. C. Xuchen Yao, Benjamin Van Durme and C. Callison-Burch. Answer extraction as sequence tagging with tree edit distance. In NAACL, 2013.
    • (2013) NAACL
    • Xuchen Yao, P.C.1    Van Durme, B.2    Callison-Burch, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.