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The Place and Role of Lexicographic Support in Information Retrieval Using Hierarchical Classifications

  • INFORMATION SEARCH
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Abstract

The role and place of lexicographic support in the issues of information retrieval with the use of hierarchical classifications based on a systematic approach using modern model representations is considered. The issues of practical application of the vocabulary lexicographic arsenal in the process of information search in a single digital space of scientific knowledge are touched upon. The sources of lexicographic diversity expansion and the features of their integration in relation to the problem of information retrieval are discussed. It is shown that the expansion of the lexicographic potential of the fields for describing concepts (classes) is mainly aimed at thematic search of information. The exception is the use of mapping tables in information retrieval, which can be directed to the path of information search by classification indices.

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REFERENCES

  1. Antopol’skii, A.B., Kalenov, N.E., Serebryakov, V.A., and Sotnikov, A.N., Common digital space of scientific knowledge, Vestn. Ross. Akad. Nauk, 2019, vol. 89, no. 7, pp. 728–735.  https://doi.org/10.31857/S0869-5873897728-735

    Article  Google Scholar 

  2. Ataeva, O.M., Kalenov, N.E., and Serebryakov, V.A., Ontological approach to the description of a common digital space of scientific knowledge, Elektron. Bibl., 2021, vol. 24, no. 1, pp. 3–19.  https://doi.org/10.26907/1562-5419-2021-24-1-3-19

    Article  Google Scholar 

  3. Skaruk, G.A., Languages of thematic search in electronic catalog and individual search interaction, Bibliosfera, 2005, no. 2, pp. 45–49.

  4. Sukiasyan, E.R., Classification system as a tool for automated search. Part 1. Why is classification search more effective than a verbal one?, Nauchn. Tekh. Bibl., 2015, no. 3, pp. 20–29.

  5. Deleuze, G. and Guattari, F., Rhizome: Introduction (Minuit, Paris, 1976), pp. 17–38.

    Google Scholar 

  6. GOST (State Standard) 7.49-84: GASNTI rubricator. Structure, rules for use and maintenance, 1984.

  7. GOST R (State Standard) 7.0.49-2007: System of standards on information, librarianship and publishing. National rubricator for scientific and technical information. Structure, rules for use and maintenance, 2008.

  8. GOST (State Standard) 7.90-2006: System of standards on information, librarianship and publishing. Universal decimal classification. Structure, rules for use and indexing, 2017.

  9. GOST (State Standard) 7.25-2001: System of standards on information, librarianship and publishing. Monolingual thesaurus for information retrieval. Rules for its development, structure, composition and form of presentation, 2002.

  10. GOST R (State Standard) ISO 15489-1-2019: System of standards on information, librarianship and publishing. Information and documentation. Records management. Part 1. Concepts and principles, 2020.

  11. Beloozerov, V.N. and Antoshkova, O.A., Development of a national standard for comparison of information retrieval languages, Nauchnoe izdanie mezhdunarodnogo urovnya-2019. Strategiya i taktika upravleniya i razvitiya (Science Periodical of International Level-2019: Strategy and Tactics of Management and Development), Kirillova, O.V., Ed., Yekaterinburg: Ural. Fed. Univ. im. El’tsina, 2019, pp. 35–43.  https://doi.org/10.24069/konf-23-26-04-2019.04

    Book  Google Scholar 

  12. GOST R (State Standard) ISO 30042-2016: Systems to manage terminology, knowledge and content. TermBase eXchange (TBX), 2017.

  13. GOST R (State Standard) ISO 704-2010: Terminology work. Principles and methods, 2011.

  14. Gusenkov, A.M., Bukharaev, N.R., and Birialtsev, E.V., Building subject domain ontology for a corporate web application, Nauchn. Servis Seti Internet, 2019, no. 21, pp. 302–317.  https://doi.org/10.20948/abrau-2019-58

  15. Medvedeva, I.B., Developing ontology of CAD systems, Inf., Vychisl. Tekh. Inzhh. Obraz., 2015, no. 3, pp. 35–41.

  16. Shebalov, R. and Gorshkov, S., Sovremennye rossiiskie razrabotki v oblasti ontologicheskogo modelirovaniya. Obzor (Modern Russian Ideas in the Area of Ontological Modeling: A Review), TriniData, 2018.

  17. ISO 25964-2:2013: Information and documentation – Thesauri and interoperability with other vocabularies – Part 2: Interoperability with other vocabularies, 2013.

  18. Baker, T., Bermès, E., Coyle, K, Dunsire, G., Isaac, A., Murray, P., Panzer, M., Schneider, J., Singer, R., Summers, Ed, Waites, W., Young, J., and Zeng, M., Library linked data Incubator Group final report: W3C Incubator Group Report 25 October 2011. http://www.w3.org/2005/Incubator/lld/XGR-lld-20111025/.

  19. Skaruk, G.A., Options for searching e-catalog by classification numbers, Nauchn. Tekh. Bibl., 2016, no. 3, pp. 19–29.  https://doi.org/10.33186/1027-3689-2016-3-19-29

  20. Szomszor, M., Adams, J., Pendlebury, D.A., and Rogers G., Global Research Report – Data Categorization: Understanding Choices and Outcomes, London: Clarivate, 2021.

    Google Scholar 

  21. Antopol’skii, A.B., Beloozerov, B.N., Makarova, T.S., and Dmitrieva, E.Yu., Matching rubrics of GRNTI and rubrics of other classification systems, Nauchn.-Tekhn. Inform., Ser. 1. Organ. Metod. Inf. Rab., 2015, no. 3, pp. 23–26.

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Authors and Affiliations

  1. All-Russian Institute of Scientific and Technical Information, Moscow, Russia

    A. V. Metlova, T. S. Astakhova & A. N. Sysoev

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  1. A. V. Metlova
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  2. T. S. Astakhova
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  3. A. N. Sysoev
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Correspondence to A. V. Metlova, T. S. Astakhova or A. N. Sysoev.

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Translated by L. Solovyova

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Metlova, A.V., Astakhova, T.S. & Sysoev, A.N. The Place and Role of Lexicographic Support in Information Retrieval Using Hierarchical Classifications. Autom. Doc. Math. Linguist. 56, 63–69 (2022). https://doi.org/10.3103/S0005105522020030

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