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Artificial Intelligence and Decision Making, 2018, Issue 2, Pages 47–61
DOI: https://doi.org/10.14357/20718594180204 (Mi iipr206) 		 
This article is cited in 1 scientific paper (total in 1 paper)

Natural language processing

Open information extraction. Part I. The task and the review of the state of the art

A. O. Shelmanov, V. A. Isakov, M. A. Stankevich, I. V. Smirnov

Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
Full-text PDF (472 kB) Citations (1)
DOI: https://doi.org/10.14357/20718594180204
Abstract: The paper discusses the task of open information extraction from natural language texts. Open information extraction – is rather new approach to solving tasks of information extraction that do not specify structure and semantics of the information to be extracted. This approach is domain independent and does not require big annotated corpora. We present the formulation of the problem and review the state of the art related to extraction of entities and semantic relations from texts including methods of information extraction based on semi-supervised and unsupervised learning. We present the future directions of research of methods for relation extraction based on unsupervised learning.
Keywords: open information extraction, semantic relations, term extraction, unsupervised learning, semi-supervised learning.
Funding agency Grant number
Russian Science Foundation 14-11-00692
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. O. Shelmanov, V. A. Isakov, M. A. Stankevich, I. V. Smirnov, “Open information extraction. Part I. The task and the review of the state of the art”, Artificial Intelligence and Decision Making, 2018, no. 2, 47–61
Citation in format AMSBIB
\Bibitem{SheIsaSta18}
\by A.~O.~Shelmanov, V.~A.~Isakov, M.~A.~Stankevich, I.~V.~Smirnov
\paper Open information extraction. Part~I. The task and the review of the state of the art
\jour Artificial Intelligence and Decision Making
\yr 2018
\issue 2
\pages 47--61
\mathnet{http://mi.mathnet.ru/iipr206}
\crossref{https://doi.org/10.14357/20718594180204}
\elib{https://elibrary.ru/item.asp?id=35125456}
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  • https://www.mathnet.ru/eng/iipr206
  • https://www.mathnet.ru/eng/iipr/y2018/i2/p47
    Cycle of papers
    This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Artificial Intelligence and Decision Making
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    Full-text PDF :21
    References:1
     
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