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Ontology-Driven Processing of Unstructured Text

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Artificial Intelligence (RCAI 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1093))

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Abstract

A lot of projects on ontologies focus on describing some aspect of reality: objects, relations, states of affairs, events, and processes in the world. Another approach is using ontologies for problem-solving. In this paper we discuss an approach for designing NLP tasks based on a multilevel system of ontological models. We developed a system of ontological models which is used for ontology-driven computational processing of unstructured texts. The components of the system are the ontology of task designing, the ontology of applied models, and the domain ontology. We discuss the general schema of designing solutions of applied tasks and some applications.

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Acknowledgments

This work was funded by the subsidy allocated to Kazan Federal University for the state assignment in the sphere of scientific activities, grant agreement no. 1.2368.2017.

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Authors and Affiliations

  1. Tatarstan Academy of Sciences, Bauman Street, 20, Kazan, 420111, Russia

    Olga Nevzorova

  2. Kazan Federal University, Kremlevskaja Street, 18, Kazan, 420008, Russia

    Olga Nevzorova

  3. Kazan National Research Technical University n.a. A.N. Tupolev, K. Marks Street, 10, Kazan, 420111, Russia

    Vladimir Nevzorov

Authors
  1. Olga Nevzorova
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  2. Vladimir Nevzorov
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Corresponding author

Correspondence to Olga Nevzorova .

Editor information

Editors and Affiliations

  1. National Research University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  2. Artificial Intelligence Research Institute, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia

    Aleksandr I. Panov

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Nevzorova, O., Nevzorov, V. (2019). Ontology-Driven Processing of Unstructured Text. In: Kuznetsov, S., Panov, A. (eds) Artificial Intelligence. RCAI 2019. Communications in Computer and Information Science, vol 1093. Springer, Cham. https://doi.org/10.1007/978-3-030-30763-9_11

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  • DOI: https://doi.org/10.1007/978-3-030-30763-9_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30762-2

  • Online ISBN: 978-3-030-30763-9

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