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J-GLOBAL ID:201802266509907218   Reference number:18A0950312

Semantically Readable Distributed Representation Learning and Its Expandability Using a Word Semantic Vector Dictionary

単語意味的ベクトル辞書を用いた意味的に読取り可能な分散表現学習とその拡張性
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Material:
Volume: E101.D  Issue:Page: 1066-1078(J-STAGE)  Publication year: 2018 
JST Material Number: U0469A  ISSN: 1745-1361  Document type: Article
Article type: 原著論文  Country of issue: Japan (JPN)  Language: ENGLISH (EN)
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Semi thesaurus term:
Thesaurus term/Semi thesaurus term
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Natural language processing  ,  Applied psychology  ,  Artificial intelligence 
Reference (24):
  • [1] I. Keshi, Y. Suzuki, K. Yoshino, and S. Nakamura, “Semantically readable distributed representation learning for social media mining,” Proc. IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp.716-722, 2017.
  • [2] T. Mikolov, K. Chen, G. Corrado, and J. Dean, “Efficient estimation of word representations in vector space,” CoRR, vol.abs/1301.3781, 2013.
  • [3] T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean, “Distributed representations of words and phrases and their compositionality,” CoRR, vol.abs/1310.4546, 2013.
  • [4] T. Mikolov, W. Yih, and G. Zweig, “Linguistic regularities in continuous space word representations,” Proc. NAACL, pp.746-751, 2013.
  • [5] Q.V. Le and T. Mikolov, “Distributed representations of sentences and documents,” Proc. ICML, pp.1188-1196, 2014.
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