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Volumn SS-15-03, Issue , 2015, Pages 10-13

Learning distributed word representations for natural logic reasoning

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER CIRCUITS; KNOWLEDGE REPRESENTATION; SEMANTICS;

EID: 84987608736     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (23)

References (23)
  • 1
    • 84990056270 scopus 로고    scopus 로고
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    • Baroni, M.; Bernardi, R.; Do, N.-Q.; and Shan, C.-c. 2012. Entailment above the word level in distributional semantics. In Proc. EACL.
    • (2012) Proc. EACL
    • Baroni, M.1    Bernardi, R.2    Do, N.-Q.3    Shan, C.-C.4
  • 3
    • 85083952458 scopus 로고    scopus 로고
    • Learning new facts from knowledge bases with neural tensor networks and semantic word vectors
    • Chen. D.: Socher. R.; Manning, C; and Ng. A. 2013. Learning new facts from knowledge bases with neural tensor networks and semantic word vectors. In Proc. ICLR.
    • (2013) Proc. ICLR
    • Chen, D.1    Socher, R.2    Manning, C.3    Ng, A.4
  • 4
    • 84862218234 scopus 로고    scopus 로고
    • Mathematical foundations for a compositional distributed model of meaning
    • Clark. S.; Coecke, B.; and Sadrzadeh, M. 2011. Mathematical foundations for a compositional distributed model of meaning. Linguistic Analysis 36(1-4):345-384.
    • (2011) Linguistic Analysis , vol.36 , Issue.1-4 , pp. 345-384
    • Clark, S.1    Coecke, B.2    Sadrzadeh, M.3
  • 6
    • 80052250414 scopus 로고    scopus 로고
    • Adaptive subgra-dient methods for online learning and stochastic optimization
    • Duchi, J.; Hazan, E.; and Singer, Y. 2011. Adaptive subgra-dient methods for online learning and stochastic optimization. JMLR.
    • (2011) JMLR
    • Duchi, J.1    Hazan, E.2    Singer, Y.3
  • 11
    • 0344671619 scopus 로고    scopus 로고
    • Approximating the semantics of logic programs by recurrent neural networks
    • Holldobler, S.; Kalinke, Y.; and Storr, H.-P. 1999. Approximating the semantics of logic programs by recurrent neural networks. Applied Intelligence 11(1).
    • (1999) Applied Intelligence , vol.11 , Issue.1
    • Holldobler, S.1    Kalinke, Y.2    Storr, H.-P.3
  • 14
    • 0004225459 scopus 로고
    • New York: Harper & Row
    • Katz, .1. J. 1972. Semantic Theory. New York: Harper & Row.
    • (1972) Semantic Theory
    • Katz, J.1
  • 15
    • 84893676344 scopus 로고    scopus 로고
    • Rectifier nonlin-earities improve neural network acoustic models
    • Maas. A.; Hannun, A.; and Ng. A. 2013. Rectifier nonlin-earities improve neural network acoustic models. In Proc. ICML.
    • (2013) Proc. ICML
    • Maas, A.1    Hannun, A.2    Ng, A.3
  • 16
  • 17
    • 84976702763 scopus 로고
    • WordNet: A lexical database for English
    • Miller, G. A. 1995. WordNet: A lexical database for English. Communications of the ACM 38(11):39-41.
    • (1995) Communications of the ACM , vol.38 , Issue.11 , pp. 39-41
    • Miller, G.A.1
  • 19
    • 84973527850 scopus 로고    scopus 로고
    • Looking for hyponyms in vector space
    • Rei, M. and Briscoe, T. 2014. Looking for hyponyms in vector space. In Proc. CoNLL.
    • (2014) Proc. CoNLL
    • Rei, M.1    Briscoe, T.2
  • 21
    • 80053261327 scopus 로고    scopus 로고
    • Semi-supervised recursive autoencodcrs for predicting sentiment distributions
    • Socher. R.: Pennington. J.; Huang. H.; Ng. A.; and Manning. C. 2011. Semi-supervised recursive autoencodcrs for predicting sentiment distributions. In Proc. EMNLP.
    • (2011) Proc. EMNLP
    • Socher, R.1    Pennington, J.2    Huang, H.3    Ng, A.4    Manning, C.5
  • 22
    • 84928547704 scopus 로고    scopus 로고
    • Sequence to sequence learning with neural networks
    • Sutskever, I.; Vinyals, O.: and Le, Q. 2014. Sequence to sequence learning with neural networks. In Proc. NIPS.
    • (2014) Proc. NIPS.
    • Sutskever, I.1    Vinyals, O.2    Le, Q.3
  • 23


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.