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Volumn , Issue , 2015, Pages

Embedding entities and relations for learning and inference in knowledge bases

Author keywords

[No Author keywords available]

Indexed keywords

SEMANTICS;

EID: 85083951274     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (2284)

References (35)
  • 2
    • 85120807674 scopus 로고    scopus 로고
    • Learning structured embeddings of knowledge bases
    • Bordes, Antoine, Weston, Jason, Collobert, Ronan, and Bengio, Yoshua. Learning structured embeddings of knowledge bases. In AAAI, 2011.
    • (2011) AAAI
    • Bordes, A.1    Weston, J.2    Collobert, R.3    Bengio, Y.4
  • 3
    • 84877727208 scopus 로고    scopus 로고
    • A semantic matching energy function for learning with multi-relational data
    • Bordes, Antoine, Glorot, Xavier, Weston, Jason, and Bengio, Yoshua. A semantic matching energy function for learning with multi-relational data. Machine Learning, pp. 1–27, 2013a.
    • (2013) Machine Learning , pp. 1-27
    • Bordes, A.1    Glorot, X.2    Weston, J.3    Bengio, Y.4
  • 5
    • 85083952396 scopus 로고    scopus 로고
    • Can recursive neural tensor networks learn logical reasoning?
    • Bowman, Samuel R. Can recursive neural tensor networks learn logical reasoning? In ICLR, 2014.
    • (2014) ICLR
    • Bowman, S.R.1
  • 6
    • 84961295001 scopus 로고    scopus 로고
    • Typed tensor decomposition of knowledge bases for relation extraction
    • Chang, Kai-Wei, Yih, Wen-tau, Yang, Bishan, and Meek, Chris. Typed tensor decomposition of knowledge bases for relation extraction. In EMNLP, 2014.
    • (2014) EMNLP
    • Chang, K.-W.1    Yih, W.-T.2    Yang, B.3    Meek, C.4
  • 7
    • 84890526837 scopus 로고    scopus 로고
    • New types of deep neural network learning for speech recognition and related applications: An overview
    • Deng, Li, Hinton, G., and Kingsbury, B. New types of deep neural network learning for speech recognition and related applications: An overview. In in ICASSP, 2013.
    • (2013) ICASSP
    • Deng, L.1    Hinton, G.2    Kingsbury, B.3
  • 8
    • 80052250414 scopus 로고    scopus 로고
    • Adaptive subgradient methods for online learning and stochastic optimization
    • Duchi, John, Hazan, Elad, and Singer, Yoram. Adaptive subgradient methods for online learning and stochastic optimization. The Journal of Machine Learning Research, 12:2121–2159, 2011.
    • (2011) The Journal of Machine Learning Research , vol.12 , pp. 2121-2159
    • Duchi, J.1    Hazan, E.2    Singer, Y.3
  • 9
    • 84880561534 scopus 로고    scopus 로고
    • Amie: Association rule mining under incomplete evidence in ontological knowledge bases
    • Galárraga, Luis Antonio, Teflioudi, Christina, Hose, Katja, and Suchanek, Fabian. Amie: association rule mining under incomplete evidence in ontological knowledge bases. In WWW, 2013.
    • (2013) WWW
    • Galárraga, L.A.1    Teflioudi, C.2    Hose, K.3    Suchanek, F.4
  • 10
    • 85106623891 scopus 로고    scopus 로고
    • Modeling interestingness with deep neural networks
    • Gao, Jianfeng, Pantel, Patrick, Gamon, Michael, He, Xiaodong, Deng, Li, and Shen, Yelong. Modeling interestingness with deep neural networks. In EMNLP, 2014.
    • (2014) EMNLP
    • Gao, J.1    Pantel, P.2    Gamon, M.3    He, X.4    Deng, L.5    Shen, Y.6
  • 11
    • 84907008976 scopus 로고    scopus 로고
    • Effective blending of two and three-way interactions for modeling multi-relational data
    • Springer
    • García-Durán, Alberto, Bordes, Antoine, and Usunier, Nicolas. Effective blending of two and three-way interactions for modeling multi-relational data. In Machine Learning and Knowledge Discovery in Databases, pp. 434–449. Springer, 2014.
    • (2014) Machine Learning and Knowledge Discovery in Databases , pp. 434-449
    • García-Durán, A.1    Bordes, A.2    Usunier, N.3
  • 13
    • 85021645803 scopus 로고    scopus 로고
    • Towards a formal distributional semantics: Simulating logical calculi with tensors
    • Grefenstette, Edward. Towards a formal distributional semantics: Simulating logical calculi with tensors. In *SEM, 2013.
    • (2013) SEM
    • Grefenstette, E.1
  • 15
    • 84889566627 scopus 로고    scopus 로고
    • Learning deep structured semantic models for web search using clickthrough data
    • Huang, Po-Sen, He, Xiaodong, Gao, Jianfeng, Deng, Li, Acero, Alex, and Heck, Larry. Learning deep structured semantic models for Web search using clickthrough data. In CIKM, 2013.
    • (2013) CIKM
    • Huang, P.-S.1    He, X.2    Gao, J.3    Deng, L.4    Acero, A.5    Heck, L.6
  • 17
    • 84877742658 scopus 로고    scopus 로고
    • A latent factor model for highly multi-relational data
    • Jenatton, Rodolphe, Le Roux, Nicolas, Bordes, Antoine, and Obozinski, Guillaume. A latent factor model for highly multi-relational data. In NIPS, 2012.
    • (2012) NIPS
    • Jenatton, R.1    Le Roux, N.2    Bordes, A.3    Obozinski, G.4
  • 18
    • 34247470526 scopus 로고    scopus 로고
    • Learning systems of concepts with an infinite relational model
    • Kemp, Charles, Tenenbaum, Joshua B, Griffiths, Thomas L, Yamada, Takeshi, and Ueda, Naonori. Learning systems of concepts with an infinite relational model. In AAAI, volume 3, pp. 5, 2006.
    • (2006) AAAI , vol.3 , pp. 5
    • Kemp, C.1    Tenenbaum, J.B.2    Griffiths, T.L.3    Yamada, T.4    Ueda, N.5
  • 19
    • 84898956512 scopus 로고    scopus 로고
    • Distributed representations of words and phrases and their compositionality
    • Mikolov, Tomas, Sutskever, Ilya, Chen, Kai, Corrado, Greg S, and Dean, Jeff. Distributed representations of words and phrases and their compositionality. In NIPS, pp. 3111–3119, 2013.
    • (2013) NIPS , pp. 3111-3119
    • Mikolov, T.1    Sutskever, I.2    Chen, K.3    Corrado, G.S.4    Dean, J.5
  • 20
    • 80053444720 scopus 로고    scopus 로고
    • A three-way model for collective learning on multi-relational data
    • Nickel, Maximilian, Tresp, Volker, and Kriegel, Hans-Peter. A three-way model for collective learning on multi-relational data. In ICML, pp. 809–816, 2011.
    • (2011) ICML , pp. 809-816
    • Nickel, M.1    Tresp, V.2    Kriegel, H.-P.3
  • 21
    • 84860859524 scopus 로고    scopus 로고
    • Factorizing yago: Scalable machine learning for linked data
    • Nickel, Maximilian, Tresp, Volker, and Kriegel, Hans-Peter. Factorizing YAGO: scalable machine learning for linked data. In WWW, pp. 271–280, 2012.
    • (2012) WWW , pp. 271-280
    • Nickel, M.1    Tresp, V.2    Kriegel, H.-P.3
  • 22
    • 0035271945 scopus 로고    scopus 로고
    • Learning distributed representations of concepts using linear relational embedding
    • Paccanaro, Alberto and Hinton, Geoffrey E. Learning distributed representations of concepts using linear relational embedding. IEEE Transactions on Knowledge and Data Engineering, 13(2): 232–244, 2001.
    • (2001) IEEE Transactions on Knowledge and Data Engineering , vol.13 , Issue.2 , pp. 232-244
    • Paccanaro, A.1    Hinton, G.E.2
  • 23
    • 32044466073 scopus 로고    scopus 로고
    • Markov logic networks
    • Richardson, Matthew and Domingos, Pedro. Markov logic networks. Machine learning, 62(1-2): 107–136, 2006.
    • (2006) Machine Learning , vol.62 , Issue.1-2 , pp. 107-136
    • Richardson, M.1    Domingos, P.2
  • 25
  • 26
    • 84928315948 scopus 로고    scopus 로고
    • A latent semantic model with convolutional-pooling structure for information retrieval
    • Shen, Yelong, He, Xiaodong, Gao, Jianfeng, Deng, Li, and Mesnil, Gregoire. A latent semantic model with convolutional-pooling structure for information retrieval. In CIKM, 2014a.
    • (2014) CIKM
    • Shen, Y.1    He, X.2    Gao, J.3    Deng, L.4    Mesnil, G.5
  • 27
    • 84990946747 scopus 로고    scopus 로고
    • Learning semantic representations using convolutional neural networks for web search
    • Shen, Yelong, He, Xiaodong, Gao, Jianfeng, Deng, Li, and Mesnil, Grégoire. Learning semantic representations using convolutional neural networks for Web search. In WWW, pp. 373–374, 2014b.
    • (2014) WWW , pp. 373-374
    • Shen, Y.1    He, X.2    Gao, J.3    Deng, L.4    Mesnil, G.5
  • 28
    • 65449121541 scopus 로고    scopus 로고
    • Relational learning via collective matrix factorization
    • ACM
    • Singh, Ajit P and Gordon, Geoffrey J. Relational learning via collective matrix factorization. In KDD, pp. 650–658. ACM, 2008.
    • (2008) KDD , pp. 650-658
    • Singh, A.P.1    Gordon, G.J.2
  • 29
    • 84870715081 scopus 로고    scopus 로고
    • Semantic compositionality through recursive matrix-vector spaces
    • Socher, Richard, Huval, Brody, Manning, Christopher D., and Ng, Andrew Y. Semantic compositionality through recursive matrix-vector spaces. In EMNLP-CoNLL, 2012.
    • (2012) EMNLP-CoNLL
    • Socher, R.1    Huval, B.2    Manning, C.D.3    Ng, A.Y.4
  • 30
    • 84898956227 scopus 로고    scopus 로고
    • Reasoning with neural tensor networks for knowledge base completion
    • Socher, Richard, Chen, Danqi, Manning, Christopher D., and Ng, Andrew Y. Reasoning with neural tensor networks for knowledge base completion. In NIPS, 2013.
    • (2013) NIPS
    • Socher, R.1    Chen, D.2    Manning, C.D.3    Ng, A.Y.4
  • 31
    • 35148867982 scopus 로고    scopus 로고
    • YAGO: A core of semantic knowledge
    • Suchanek, Fabian M, Kasneci, Gjergji, and Weikum, Gerhard. Yago: a core of semantic knowledge. In WWW, 2007.
    • (2007) WWW
    • Suchanek, F.M.1    Kasneci, G.2    Weikum, G.3
  • 32
    • 84858720748 scopus 로고    scopus 로고
    • Modelling relational data using bayesian clustered tensor factorization
    • Sutskever, Ilya, Tenenbaum, Joshua B, and Salakhutdinov, Ruslan. Modelling relational data using Bayesian clustered tensor factorization. In NIPS, pp. 1821–1828, 2009.
    • (2009) NIPS , pp. 1821-1828
    • Sutskever, I.1    Tenenbaum, J.B.2    Salakhutdinov, R.3
  • 33
    • 84877777313 scopus 로고    scopus 로고
    • Learning with recursive perceptual representations
    • Vinyals, O., Jia, Y., Deng, L., and Darrell, T. Learning with recursive perceptual representations. In NIPS, 2012.
    • (2012) NIPS
    • Vinyals, O.1    Jia, Y.2    Deng, L.3    Darrell, T.4
  • 34
    • 84906930320 scopus 로고    scopus 로고
    • Semantic parsing for single-relation question answering
    • Yih, Wen-tau, He, Xiaodong, and Meek, Christopher. Semantic parsing for single-relation question answering. In ACL, 2014.
    • (2014) ACL
    • Yih, W.-T.1    He, X.2    Meek, C.3
  • 35
    • 84871387302 scopus 로고    scopus 로고
    • The deep tensor neural network with applications to large vocabulary speech recognition
    • Yu, D., Deng, L., and Seide, F. The deep tensor neural network with applications to large vocabulary speech recognition. IEEE Trans. Audio, Speech and Language Proc., 21(2):388 –396, 2013.
    • (2013) IEEE Trans. Audio, Speech and Language Proc. , vol.21 , Issue.2 , pp. 388-396
    • Yu, D.1    Deng, L.2    Seide, F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.