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E. V. Degtiareva, E. N. Kruchkova Models and Methods for Automatic Comparative Semantic Analysis of Scientific Texts |
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Abstract.
The article considers a general approach to the implementation of algorithms for comparative analysis of scientific texts from the position of their general content and from the position of dynamic sequence of text fragment semantics. The proposed algorithms for comparative analysis of scientific texts are based on the clustering of semantic graphs, which are constructed as a result of combining information extracted from the publication with the scientific domain semantics. Approaches to extracting a dynamic subsequence of semantically similar fragments are discussed, and ways of calculating correlation coefficients are given. The paper presents experimental results of static and dynamic comparative analysis of mathematical publications, which are graphically illustrated.
Keywords:
aspect-oriented analysis, scientific vocabulary, semantic graph, classification of scientific text.
DOI 10.14357/20718632250302
EDN KYTZUH
PP. 13-21.
References
1. Bruches E.P., Batura T.V. Method for Automatic Term Extraction from Scientific Articles Based on Weak Supervision. Vestnik NSU, Series: Information Technologies. 2021; 19(2): 5-16. (In Russ.). DOI: 10.25205/1818-7900-2021-19-2-5-16. 2. Morozov D. A., Glazkova A. V., Tyutyulnikov M. A., Iomdin B. L. Keyphrase Generation for Abstracts of the Russian-Language Scientific Articles, Vestnik NSU, Series: Linguistics and Intercultural Communication. 2023; 21(1): 54-66. (In Russ.). DOI: 10.25205/1818-7935-2023-21- 1-54-66. 3. Altmami N., Menai M. Automatic Summarization of Scientific Articles: A Survey // Journal of King Saud University - Computer and Information Sciences. 2020; 34: 1011-1028. DOI:10.1016/j.jksuci.2020.04.020. 4. Benites F. Information Retrieval and Knowledge Extraction for Academic Writing // Digital Writing Technologies in Higher Education. 2023; 303-315. DOI: 10.1007/978-3-031-36033- 6_19. 5. Qurashi A. W., Holmes V., Johnson A. P. Document Processing: Methods for Semantic Text Similarity Analysis. International Conference on INnovations in Intelligent SysTems and Applications, Serbia. 2020: 1-6. DOI: 10.1109/INISTA49547.2020.9194665. 6. Sanchez-Gomez J. M., Vega-Rodríguez M. A., Pérez C. J. The impact of term-weighting schemes and similarity measures on extractive multi-document text summarization. Expert Systems with Applications. 2021; 169. DOI: 10.1016/j.eswa.2020.114510. 7. Seki K. Cross-lingual text similarity exploiting neural machine translation models. Journal of Information Science. 2021; 47(3): 404–418. DOI:10.1177/01655515209126768. Ji M., Zhang X. A Short Text Similarity Calculation Method Combining Semantic and Headword Attention Mechanism. Scientific Programming. 2022; Available from: https://onlinelibrary.wiley.com/ doi/10.1155/2022/8252492. 9. Inan E. SimiT: A Text Similarity Method Using Lexicon and Dependency Representations. New Generation Computing. 2020; 38(3): 509–530. DOI:10.1007/s00354-020-00099-8. 10. Islam A., Inkpen D. Semantic text similarity using corpusbased word similarity and string similarity. ACM Transactions on Knowledge Discovery from Data. 2008; Available from: https://www.academia.edu/4418471/Semantic_text_similarity_using_corpus_ based_word_similarity_and_string_similarity. 11. Vopilova E.V., Kruchkova E.N. automatic analysis methods of dynamics of information presentation in texts based on adaptable dictionaries of scientific terms. Programmnaya inzheneriya. 2024; 15(4): 206-215. (In Russ.). DOI: 10.17587/prin.15.206-215. 12. Vopilova E.V., Kruchkova E.N. Methods and algorithms for automatic extraction of information from scientific texts for creating a scientific terminology thesaurus. Intellektualnye sistemy. Teoriya i prilozheniya. 2024; 28(4). (In Russ.). 13. Vinogradov I.M., Ed. Mathematical encyclopedia in 5 volumes. M: Sovetskaya enciklopediya, 1977. 14. Zagrebina S. A., Ed. Vestnik YUzhno-Ural'skogo universiteta, seriya «Matematika. Mekhanika. Fizika». 2022; 14(2-4). 15. Matematicheskij sbornik. 2022; 213(9-12).
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