Preview

Scientific and Technical Libraries

Advanced search

Avenues for artificial intelligence in library and information services

https://doi.org/10.33186/1027-3689-2025-1-120-134

Abstract

The author discusses the key concepts of the artificial intelligence, computerized analysis and machine learning. The chatbots СhatGPT, GigaChat, Alisa can be used in the libraries and information centers to assist in translations of foreign publications, article reviewing, etc. The author examines the possibility of integrating chatbot into the websites to render the first assistance to the users, in particular beyond office hours. The author reviews using AI for literature system reviewing and argues that the selection process is more efficient, and time is saved. He demonstrates the AI capabilities to improve the relevance of response to the search queries in the library computerized systems and to develop user personal account services. The latter would enable to generate personalized recommendations for articles, patents and reviews within the subject scope of studies and to select the most relevant materials for publication. For the system proper operation, the author suggests to develop the system for evaluation of the produced materials and services quality. Based on this system and requested materials, the personalized analytical and recommendation system can be generated to identify the lines of further research and development. Despite underdeveloped technologies, impossibility of total replacement of the humans, high implementation costs, etc., the AI methods and algorithms of learning and analysis enable to computerize several information processing operations, to reveal patterns and trends, t o p redict u ser n eeds, w hich l ays t he w ay f or d eveloping a nd i mproving services in the libraries and information centers

About the Author

I. A. Mitroshin
Library for Natural Science, Russian Academy of Science
Russian Federation

Ivan A. Mitroshin – Senior Researcher

Moscow



References

1. Neshcheret M. Iu. Nei`roseti v biblioteke: novoe v bibliograficheskom obsluzhivanii // Nauchny`e i tekhnicheskie biblioteki. 2024. № 1. S. 105–128. https://doi.org/10.33186/1027-3689-2024-1-105-128.

2. Shrayberg Ya. L., Boronina N. V. The Capabilities of a Research Library to Enhance Cultural and Leisure Activities in the Digital Environment: Foreign Experience and Domestic Reality // Scientific and Technical Information Processing. 2021. Vol. 48, № 4. P. 284–289.

3. Shrai`berg Ia. L. Tcifrovizatciia, pandemiia, e`kologiia iazy`ka, ry`nok informatcionny`kh i obrazovatel`ny`kh uslug i biblioteki: kurs na vy`zhivanie i ustoi`chivoe razvitie : Ezhegodny`i` doclad Shestogo mezhdunarodnogo professional`nogo foruma «Kry`m-2021» // Nauchny`e i tekhnicheskie biblioteki. 2021. № 9. C. 13–72.

4. Boronina N. V. IRNP-deiatel`nost` kak neot``emlemaia chast` deiatel`nosti nauchny`kh bibliotek v e`pohu tcifrovizatcii obshchestva // Nauchny`e i tekhnicheskie biblioteki. 2022. № 4. C. 78–89.

5. Young J. C., Boyd B., Yefimova K., Wedlake S., Coward Ch., Hapel R. The role of libraries in misinformation programming: a research agenda // Journal of Librarianship and Information Science. 2020. Vol. 53, № 4. Р. 539–550. DOI 10.1177/0961000620966650.

6. Savin G. I. Edinoe tcifrovoe prostranstvo nauchny`kh znanii`: tceli i zadachi // Informatcionny`e resursy` Rossii. 2020. № 5. S. 3–5.

7. Mitroshin I. A. Populiarizatciia nauki v nauchny`kh i tekhnicheskikh bibliotekakh // Biblioteka i kul`turnoe prostranstvo regiona: materialy` III Vserossii`skoi` nauchnoprakticheskoi` konferentcii : v 2 ch. Perm`, 10–11 noiabria 2022 g. Perm` : Permskii` gosudarstvenny`i` institut kul`tury`, 2023. S. 177–183.

8. De la Torre-López J., Ramírez A., Romero J. R. Artificial intelligence to automate the systematic review of scientific literature // Computing. 2023. 105. С. 2171–2194. DOI 10.1007/s00607-023-01181-x.

9. Roth S., Wermer-Colan A. Machine Learning Methods for Systematic Reviews: A Rapid Scoping Review // Delaware Journal of Public Health. 2023. Vol. 9, № 4. P. 40–47. DOI 10.32481/djph.2023.11.008.

10. Pang L., Xu J., Ai Q., Lan Y., Cheng X., Wen J. SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval // SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 2020. P. 499–508. DOI 10.1145/3397271.3401104. URL: https://arxiv.org/pdf/1912.05891 (accessed: 31.07.2024).

11. Ai Q., Wang X., Bruch S., Golbandi N., Bendersky M., Najork M. Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks // ICTIR '19: Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval. 2019. P. 85–92. DOI 10.1145/3341981.3344218. URL: https://arxiv.org/pdf/1811.04415 (accessed: 31.07.2024).

12. Wu J., Huang J., Ye Z. Learning to rank diversified results for biomedical information retrieval from multiple features // BioMedical Engineering OnLine. 2014. № 13 (Suppl 2). S3. DOI 10.1186/1475-925X-13-S2-S3.

13. Ludewig M., Mauro N., Latifi S., Jannach D. Performance comparison of neural and nonneural approaches to session-based recommendation // RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems. 2019. P. 462–466. DOI 10.1145/3298689.3347041.

14. Bi X., Qu A., Shen X. Multilayer tensor factorization with applications to recommender systems // Annals of Statistics. 2018. Vol. 46 (6B). P. 3303–3333. DOI 10.1214/17-AOS1659.

15. Bi X., Qu A., Wang J., Shen X. A group-specific recommender system // Journal of the American Statistical Association. 2017. V. 112 (519). P. 1344–1353. DOI 10.1080/01621459.2016.1219261.

16. Pary`gin D. S., Strekalova A. S., Gurtiakov A. S., Adannia S. G., Pivovarov V. V. Primenenie rekomendatel`ny`kh tekhnologii` v sistemakh s prostranstvennoi` informatciei` // Prikaspii`skii` zhurnal: upravlenie i vy`sokie tekhnologii. 2019. T. 45, № 1. S. 96–109.

17. Mitroshin I. A. Prodvizhenie sai`ta nauchnoi` biblioteki // Nauchny`e i tekhnicheskie biblioteki. 2022. № 10. S. 115–129. DOI 10.33186/1027-3689-2022-10-115-129.

18. Mitroshin I. A. Informatcionnaia podderzhka bibliotekami innovatcionnoi` deiatel`nosti: opy`t Biblioteki po estestvenny`m naukam RAN // Upravlenie naukoi`: teoriia i praktika. 2023. T. 5, № 3. S. 169–184. DOI 10.19181/smtp.2023.5.3.11.

19. Zemskov A. I., Telitcy`na A. Iu. Demonstratciia vozmozhnostei` chata GPT v bibliotechnoi` deiatel`nosti // Nauchny`e i tekhnicheskie biblioteki. 2024. № 4. S. 131–145. DOI 10.33186/1027-3689-2024-4-131-145.

20. Moiseeva N. A. Tekhnologii iskusstvennogo intellekta v informatcionno-bibliotechny`kh sistemakh // Nauchny`e i tekhnicheskie biblioteki. 2024. № 5. S. 85–101. DOI 10.33186/1027-3689-2024-5-85-101.


Review

For citations:


Mitroshin I.A. Avenues for artificial intelligence in library and information services. Scientific and Technical Libraries. 2025;(1):120-134. (In Russ.) https://doi.org/10.33186/1027-3689-2025-1-120-134

Views: 590


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1027-3689 (Print)
ISSN 2686-8601 (Online)