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Volumn , Issue , 2016, Pages 2537-2547

Table filling multi-task recurrent neural network for joint entity and relation extraction

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; EXTRACTION; NETWORK ARCHITECTURE; RECURRENT NEURAL NETWORKS; SEMANTICS;

EID: 85050264296     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (317)

References (27)
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    • Multitask learning
    • Rich Caruana. 1998. Multitask learning. Springer.
    • (1998) Springer
    • Caruana, R.1
  • 4
    • 56449095373 scopus 로고    scopus 로고
    • A unified architecture for natural language processing: Deep neural networks with multitask learning
    • Helsinki, Finland
    • Ronan Collobert and Jason Weston. 2008. A unified architecture for natural language processing: deep neural networks with multitask learning. In Proceedings of the 25th International Conference on Machine Learning, Helsinki, Finland.
    • (2008) Proceedings of the 25th International Conference on Machine Learning
    • Collobert, R.1    Weston, J.2
  • 8
    • 26444565569 scopus 로고
    • Finding structure in time
    • Jeffrey L Elman. 1990. Finding structure in time. Cognitive science, 14(2).
    • (1990) Cognitive Science , vol.14 , Issue.2
    • Elman, J.L.1
  • 10
    • 0004121079 scopus 로고
    • Published in Tech. Rep. No. 8604. San Diego: University of California, Institute for Cognitive Science
    • M. Jordan. 1986. Serial order: A parallel distributed processing approach. Published in Tech. Rep. No. 8604. San Diego: University of California, Institute for Cognitive Science.
    • (1986) Serial Order: A Parallel Distributed Processing Approach
    • Jordan, M.1
  • 22
    • 84994104524 scopus 로고    scopus 로고
    • Combining recurrent and convolution neural networks for relation classification
    • Ngoc Thang Vu, Heike Adel, Pankaj Gupta, and Hinrich Schütze. 2016a. Combining recurrent and convolution neural networks for relation classification. In Proceedings of the NAACL.
    • (2016) Proceedings of the NAACL
    • Vu, N.T.1    Adel, H.2    Gupta, P.3    Schütze, H.4
  • 24
    • 0025503558 scopus 로고
    • Backpropagation through time: What it does and how to do it
    • Paul J Werbos. 1990. Backpropagation through time: what it does and how to do it. In Proceedings of the IEEE.
    • (1990) Proceedings of the IEEE
    • Werbos, P.J.1
  • 25
    • 84959862537 scopus 로고    scopus 로고
    • Relation classification via convolutional deep neural network
    • Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou, and Jun Zhao. 2014. Relation classification via convolutional deep neural network. In Proceedings of COLING.
    • (2014) Proceedings of COLING
    • Zeng, D.1    Liu, K.2    Lai, S.3    Zhou, G.4    Zhao, J.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.