Kamsilova, Ontario, Small Format Science Texts: Keywords and Abstracts (Information Side); Isuv. loss. Pedo. University I am. AI Gerzena, 2013, no. 156, pp. 106–117.
Sheremetyeva, SO, Methods and models of automatic keyword extraction, Beston. Yuzhi-Ural. university, 2015, vol. 12, no. 1, pp. 76–81.
Google Scholar
Naukometriya i Expertiza v. Upravleni Naukoi (Scientometry and Expertise in Science Management, Proceedings), edited by DA Novikov, AI Orlov, and P.Yu Chebotarev, Moscow: IPU RAN, 2013, Specifications. Issue number 44.
Orlov, AI, Modern Issues in Science and Scientmetry, Biocosmol – Neo Aristotel, 2017, vol. 7, no. 3–4, pp. 389–410.
Great intelligence, Spravochnik (Artificial Intelligence: The Handbook), edited by Zakharov, VN, Popov, EV, Pospelov, DA, and Khoroshevsky, VF, Moscow: Radio Svyaz’, 1990, Vol. 2.
Google Scholar
Salton, G. dynamic library and information systems, Englewood Cliffs, NJ: Prentice Hall, 1975.
Google Scholar
Bollacker, KD, Lawrence, S., and Giles, CL, CiteSeer: An autonomous web agent for automatic search and identification of interesting publications. Proceedings of the 2nd International Conference on Autonomous Agents, 1998, pp. 116-123.
Cross, J., MEDLINE, PubMed, PubMed Central, and NLM; Editor’s Bull, 2006, no. 2. https://doi.org/10.1080/17521740701702115
Gündogan, E. and Kaya, M., A new hybrid paper recommendation system using deep learning, scientometrics, 2022, vol. 127, no. 7, pp. 3837-3855. https://doi.org/10.1007/s11192-022-04420-8
Bai, X., Wang, M., Lee, I. et al., Recommending scientific articles: A survey, IEEE access, 2019, vol. 7, pages 9324–9339.
Li, Z. and Zou, X., A review on personalized academic article recommendations, Calculate. Let me know. science, 2019, vol. 12, no. 1, pp. 33–43.
Kreutz, C. and Schenkel, R., Scientific article recommendation systems: A literature review of recent publications, arXiv, 2022, no. 2201.00682.
Beel, J., Gipp, B., Langer, S. et al., Introducing Mr. DLib, a machine-readable digital library. Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2011. https://doi.org/10.1145/1998076.1998187
Bogers, T. and van den Bosch, A., Recommending scientific articles using CiteUlike, Proceedings of the ACM Conference on Recommender Systems, 2008, pp. 287-290.
Gingstad, K., Jekteberg, Y., Balog, K., ArXivDigest: A Living Lab for Personalized Scientific Literature Recommendations, arXiv, 2020, no. 2009.11576.
Beel, J., Gipp, B., Langer, S., and Breitinger, C., Research paper recommendation systems: a literature review, internal. J. Digit. library, 2015, pp. 1-34.
Fee, H., Barth, J., Gremm, J. et al., Comparing the scope of academic citation databases with the scope of scientific social media: personal publication lists as a proofreading parameter; Online notification. pastor, 2015, vol. 39, pages 255–264. https://doi.org/10.1108/oir-07-2014-0159
Gollapalli, S. D. and Caragea, C., Extracting key phrases from research papers using citation networks. AAAI’14: Proceedings of the 28th AAAI Artificial Intelligence Conference, 2014, vol. 28, no. 1, pp. 1629–1635.
Chan, Ch. Afanashev, GI, Fundamental Technologies and Prospects of the Evolution of Personalized Recommendation Systems; Esio, 2022, no. 4 (67), pp. 309-320.
Zharova, MA and Tsurkov, VI, Neural Network Approaches for Recommender Systems, J. Compute. system. Science. international, 2023, vol. 62, no. 6, pp. 1048–1062. https://doi.org/10.1134/S1064230723060126
Liu, Y., Ott, M., Goyal, N. et al., RoBERTa: A Robustly Optimized BERT Pre-Training Approach, arXiv2019, no. 1907.11692.
Papagiannopoulou, E. and Tsoumakas, G., Review of Keyphrase Extraction, Wiley Interdisc. Rev. – Data Mining Knowledge Discovery, 2020, vol. 10, no. 2. https://doi.org/10.1002/widm.1339
Kulkarni, M., Mahata, D., Arora, R., Bhowmik, R., “Learning rich representations of key phrases from text.” Computational Linguistics Association Survey Results, ACL Conference Proceedings, 2022, pp. 891–906. https://doi.org/10.18653/v1/2022.findings-naacl.67
Liang, X., Wu, S., Li, M., and Li, Z., Unsupervised keyphrase extraction by jointly modeling local and global context, Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2021, pages 155–164. https://doi.org/10.18653/v1/2021.emnlp-main.14
Grootendorst, M., KeyBERT: Minimal Keyword Extraction with BERT, Zenodo, 2020. https://doi.org/10.5281/zenodo.4461265
Kozlov, PA, NA Nazarov, VO Torcheyev, Individual support system for scientific activities in small research teams. Sb.Materialov XXVII Mezhdunarodnoy Naufnotechniceskoy Konverentsy Information Systems Systems and Technologies (Proceedings of the 27th International Scientific and Technical Conference on Information Systems and Technology), Nizh. Novgorod: RE Alexeev Nizhegor. I agree. Tech. University, 2021, pages 630–635.
Kozlov, PA, Mokhov, AS, Nazarov, NA, et al., Comparative analysis of binary classifiers in a series of scientific publications, Zavod. Laboratory diagnosis. meter, 2022, vol. 88, no. 7, pp. 79–87. https://doi.org/10.26896/1028-6861-2022-88-7-79-87
