Artificial Intelligence and Decision Making
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Artificial Intelligence and Decision Making, 2019, Issue 4, Pages 61–69
DOI: https://doi.org/10.14357/20718594190407 (Mi iipr189) 		 
Natural language processing

Methods for identifying links between regulatory documents

D. A. Devyatkina, A. T. Sofronovab, I. V. Sochenkova

a Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
b Limited liability company "Technologies for Systems Analysis", Moscow, Russia
Full-text PDF (670 kB)
DOI: https://doi.org/10.14357/20718594190407
Abstract: The article proposes a new method for relationship detection (explicit and implicit) between legal documents, as well as its experimental assessment on the corpus of legal texts on information technology regulation. The method considers deep linguistic features and allows estimating topic, syntax and semantic similarity of legal texts.
Keywords: information extraction from legal documents, implicit relationship detection, relationalsituational analysis.
Funding agency Grant number
Russian Foundation for Basic Research 18-29-16022 мк
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: D. A. Devyatkin, A. T. Sofronova, I. V. Sochenkov, “Methods for identifying links between regulatory documents”, Artificial Intelligence and Decision Making, 2019, no. 4, 61–69
Citation in format AMSBIB
\Bibitem{DevSofSoc19}
\by D.~A.~Devyatkin, A.~T.~Sofronova, I.~V.~Sochenkov
\paper Methods for identifying links between regulatory documents
\jour Artificial Intelligence and Decision Making
\yr 2019
\issue 4
\pages 61--69
\mathnet{http://mi.mathnet.ru/iipr189}
\crossref{https://doi.org/10.14357/20718594190407}
\elib{https://elibrary.ru/item.asp?id=41800541}
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  • https://www.mathnet.ru/eng/iipr/y2019/i4/p61
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