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Analysis of publications on natural language processing indexed in RSCI

https://doi.org/10.20913/2618-7575-2021-4-81-92

Abstract

Natural Language Рrocessing (NLP), defined, as the general direction of artificial intelligence and mathematical linguistics, is an important tool for understanding and processing a gigantic amount of unstructured data.
Representing theoretical and practical basis for solving a large number of problems, NLP is being actively studied by scientists around the world, since it is one of the most popular areas of data science and is used in many fields of human activity. The purpose of this bibliometric analysis is to identify the main research centers, research trends, the rating of leading Russian scientists in the field of NLP, as well as to show the picture of thematic fields’ distribution of publications. The results of the analysis will allow us to determine the dynamics of NLP field development in the domestic science and will provide scientists and specialists working in the field of NLP with up-to-date information on various aspects of the considered research area.
Russian Science Citation Index (RSCI) – the main scientometric database in our country was used as the data source for scientific publications in the field of NLP search. The RSCI platform contains information on current research areas, allows you to assess the productivity of scientists, scientific communities, etc.
The presented work will be interesting to researchers in the field of NLP, since it contains actual data on the development dynamics and structure of the documentary and information flow in the field of NLP in Russia, its distribution by branches of knowledge. Besides, the conducted bibliometric analysis of documents allows us to gain information about the authors most productively working in the studied area and their affiliations, as well as about the most cited articles – this is the review of the 30 most cited publications of Russian scientists and rating of TOP-10 scientific organizations of the Russian Federation by the number of publications reflecting the main problems and scientific achievements in the field of NLP.

About the Author

L. L. Sadovskaya
State Public Scientific Technological Library of the Siberian Branch of the Russian Academy of Sciences (SPSTL SB RAS)
Russian Federation

Sadovskaya Larisa Leonidovna, Junior Researcher, Head of the Department of Reference and Information Service

Novosibirsk



References

1. Bolshakova E. I., Klyshinsky E. S., Lande D. E., Noskov A. A., Peskova O. V., Yagunova E. V. Avtomaticheskaya obrabotka tekstov na estestvennom yazyke i komp’yuternaya lingvistika [Automatic text processing in natural language and computational linguistics]. Moscow, Paragraph, 1990. 160 p. (In Russ.).

2. Sadovskaya L. L., Guskov A. E., Kosyakov D. V., Mukhamediev R. I. Text processing in natural language: a review of publications. Iskusstvennyi intellekt i prinyatie reshenii, 2021, 3: 66–86. (In Russ.).

3. Pislyakov V. V. Basic methods of evaluation of scientific knowledge by citation indicators. Sotsiologicheskii zhurnal, 2007, 1: 128–140. (In Russ.).

4. Mitrenina O .V., Nikolaev I. S., Lando T. M. Prikladnaya i komp’yuternaya lingvistika [Applied and computational linguistics]. Moscow, URSS, 2016. 320 p. (In Russ.).

5. Yatsko V. A. The subject area of computational linguistics. Vestnik Irkutskogo gosudarstvennogo lingvisticheskogo universiteta, 2014, 2: 24–35. (In Russ.).

6. Borovikova O. I., Zagorulko, Yu. A., Zagorulko G. B., Kononenko I. S., Sokolova E. G. Development of a knowledge portal on computational linguistics. KII-2008: Odinnadtsataya Nats. konf. po iskusstv. intellektu s mezhdunar. uchastiem. Moscow, 2008: 380–388. (In Russ.).

7. Nagel O. V. Corpus linguistics and its use in computerized language teaching. Yazyk i kul’tura, 2008, 4: 53–54. (In Russ.).

8. Prutskov A. V., Rozanov A. K. Methods of morphological text processing. Prikaspiiskii zhurnal: upravlenie i vysokie tekhnologii, 2014, 3: 119–133. (In Russ.).

9. Prutskov A. V. Generation and definition of word forms of natural languages based on their successive transformations. Vestnik Ryazanskogo gosudarstvennogo radiotekhnicheskogo uiversiteta, 2009, 27: 51–58. (In Russ.).

10. Solovyev V., Ivanov V. Knowledge–driven event extraction in Russian: corpus-based linguistic resources. Computational Intelligence and Neuroscience, 2016, 2016: 4183760. DOI: 10.1155/2016/4183760.

11. Batura T. V. Semantic analysis and ways of representing the meaning of a text in computational linguistics. Programmnye produkty i sistemy, 2016, 4: 45–57. DOI: 10.15827/0236-235X.116.045-057. (In Russ.).

12. Sharnin M. M., Somin N. V., Kuznetsov I. P., Morozova Yu. I., Galina I. V., Kozerenko E. B. Statistical mechanisms for the formation of associative portraits of subject areas based on natural language texts of large volumes for knowledge extraction systems. Informatika i ee primeneniya, 2013, 7(2): 92–99. (In Russ.).

13. Zolotarev O. V., Kozerenko E. B., Sharnin M. M. Principles of building models of business processes in the subject area based on natural language text processing. Vestnik Rossiiskogo novogo universiteta. Seriya: Slozhnye sistemy: modeli, analiz i upravleniye, 2014, 4: 82–88. (In Russ.).

14. Kuleshov S. V., Zaitseva A. A., Markov V. S. Associative–ontological approach to text processing in natural language. Intellectual Technologies on Transport, 2015, 4: 40–45. (In Russ.).

15. Vlasov D. Yu., Palchunov D. E., Stepanov P. A. Automation of extraction of relations between concepts from natural language texts. Vestnik Novosibirskogo gosudarstvennogo universiteta. Seriya: Informatsionnye tekhnologii, 2010, 8(3): 23–33. (In Russ.).

16. Lagutina K. Lagutina N., Boychuk E., Vorontsova I., Shlakhtina O., Balyarva O., Paramonov I., Demidov H. A survey on stylometric text features. 5th Conference of Open Innovations Association (FRUCT) (November 5-8, 2019). Helsinki, 2019: 184–195. DOI: 10.23919/FRUCT48121.2019.8981504.

17. Gorbushin D. A., Grinchenkov D. V., Mokhov V. A., Khau N. F. System analysis of approaches to solving the problem of identifying the tonality of the text. Izvestiya vysshikh uchebnykh zavedenii. Severo–Kavkazskii region. Tekhnicheskie nauki, 2016, 2: 36–41. (In Russ.).

18. Sarbasova A. N. Investigation of methods of sentimental analysis of Russian–language texts. Molodoy uchenyy, 2015, 8: 143–146. (In Russ.).

19. Suleimanov D. Sh., Gatiatullin A. R. Strukturno-funktsional’naya komp’yuternaya model’ tatarskikh morfem [Structural and functional computer model of Tatar morphemes]. Kazan’, Fen, 2003. 220 p. (In Russ.).

20. Posevkin R. V., Bessmertnyi I. A. Natural language user interface of a dialog system. Programmnye produkty i sistemy, 2016, 3: 5–9. (In Russ.).

21. Yatsko V. A. Algorithms and programs of automatic text processing. Vestnik Irkutskogo gosudarstvennogo lingvisticheskogo universiteta, 2012, 1: 150–160. (In Russ.).

22. Varlamov O. O., Lazarev V. M., Chuvikov D. A., Punam D. On the prospects of creating autonomous intelligent robots based on mivar technologies. Radiopromyshlennost’, 2016, 4: 96–105. DOI: 10.21778/2413-9599-2016-4-96-105. (In Russ.).

23. Varlamov O. O., Adamova L. E.., Eliseev D. V., Mayboroda Yu. I., Antonov P. D., Sergushin G. S., Chibirova M. O. Mivar technologies in mathematical modeling of natural language, images and human speech understanding. International Journal of Advanced Studies, 2013, 3(3): 17–23. DOI: 10.12731/2227-930X-2013-3-3.

24. Loukachevitch N. V., Lashevich G., Gerasimova A. A., Ivanov V. V., Dobrov B. V. Creating Russian WordNet by conversion. Computational linguistics and intellectual technologies: pap. of annu. conf. “Dialogue 2016” (Moscow, June 1-4, 2016). Moscow, 2016: 405–415.

25. Loukachevitch N. V., Dobrov B. V., Chetviorkin I. I. RuThes–Lite, a publicly available version of thesaurus of Russian language RuThes. Komp’yuternaya lingvistika i intellektual’nye tekhnologii: po materialam ezhegod. Mezhdunar. konf. «Dialog 2014». Moscow, 2014: 340–349.

26. Turdakov D. Astrakhantsev N., Nedumov Y., Sysoev A., Andrianov I., Mayorov V., Fedorenko D., Korshunov A., Kuznetsov S. Texterra: infrastructure for text analysis. Trudy Instituta sistemnogo programmirovaniya RAN, 2014, 26(1): 421–438. (In Russ.).

27. Kuznetsov I. P., Kozerenko E. B., Charnine M. M. The system for extracting semantic information from natural language text. MLMTA’03 : proc. of Intern. conf. on machine learning, models, technologies a. applications (June 32–26, 2003). Las Vegas, 2003: 75–80.

28. Prutskov A. V. Morphological analysis and synthesis of texts by means of transformations of word forms. Vestnik Ryazanskoi gosudarstvennoi radiotekhnicheskoi akademii, 2004, 15: 70–75. (In Russ.).

29. Anisimovich K. V., Druzhkin K. Ju., Minlos F. R., Petrova M. A., Selegey V. H., Zuev K. A. Syntactic and semantic parser based on ABBYY Compreno linguistic technologies. Komp’yuternaya lingvistika i intellektual’nye tekhnologii: po materialam ezhegod. Mezhdunar. konf. «Dialog 2012». Moscow, 2012: 91–103.

30. Kozlov P. Yu. Methods of automated analysis of short unstructured text documents. Programmnye produkty i sistemy, 2017, 1: 100–105. (In Russ.).

31. Moskvina A. D., Orlova D. N., Mitrofanova O. A. Development of a parser core for the Russian language based on NLTK libraries. Internet i sovremennoe obshchestvo: tr. ob”edin. nauch. konf. IMS-2016. Saint Petersburg, 2016: 44–54. (In Russ.).

32. Ermakov A. E. Extraction of knowledge from the text and their processing: state and prospects. Informatsionnye tekhnologii, 2009, 7: 50–55. (In Russ.).

33. Dikovitsky V. V., Shishaev M. G. Processing texts in natural language models search engines. Trudy Kol’skogo nauchnogo tsentra RAN, 2010, 3: 29–34. (In Russ.).

34. Maximov V. Yu., Klyshinski E. S., Antonov N. V. The problem of understanding artificial intelligence systems. Novye informatsionnye tekhnologii v avtomatizirovannykh sistemakh, 2016, 19: 43–60. (In Russ.).

35. Liddy E. D. Natural language processing. Encyclopedia of library and information science. New York, 2003: 2126–2136.

36. Suleimanov D. Sh. Sistemy i informatsionnye tekhnologii obrabotki estestvenno-yazykovykh tekstov na osnove pragmaticheski-orientirovannykh lingvisticheskikh modelei: avtoref. dis. … d-ra tekhn. nauk [Systems and information technologies for processing natural language texts based on pragmatically oriented linguistic models: diss. abstr.]. Kazan’, 2000. 43 p. (In Russ.).


Review

For citations:


Sadovskaya L.L. Analysis of publications on natural language processing indexed in RSCI. Proceedings of SPSTL SB RAS. 2021;(4):81-92. (In Russ.) https://doi.org/10.20913/2618-7575-2021-4-81-92

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