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Development of Mathematical Models and Methods for Recommender Systems and Natural Language Processing

Priority areas of development: IT and mathematics
2020

Publications:


Emelyanov A., Artemova E. Gapping parsing using pretrained embeddings, attention mechanism and NCRF, in: Computational Linguistics and Intellectual Technologies Papers from the Annual International Conference “Dialogue” (2019). Moscow : Издательский центр «Российский государственный гуманитарный университет», 2019. С. 203-212. 
Ekaterina A., Bakarov A., Artemov A., Burnaev E. V., Sharaev M. Data-driven models and computational tools for neurolinguistics: a language technology perspective // Journal of Cognitive Science. 2020. Vol. 1. No. 21. P. 15-52. doi
Alimova l., Tutubalina E. Multiple features for clinical relation extraction: A machine learning approach // Journal of Biomedical Informatics. 2020. Vol. 103. P. 1-9. doi
Krotova I., Aksenov S., Artemova E. A Joint Approach to Compound Splitting and Idiomatic Compound Detection, in: Proceedings of The 12th Language Resources and Evaluation Conference.: European Language Resources Association (ELRA), 2020. С. 4410-4417. 
Ivanin V., Artemova E., Batura T., Ivanov V., Sarkisyan V., Tutubalina E., Smurov I. RUREBUS-2020 Shared Task: Russian Relation Extraction for Business, in: Computational Linguistics and Intellectual Technologies Papers from the Annual International Conference “Dialogue” (2020).: Изд-во РГГУ, 2020. С. 401-416. 
Malykh V., Chernis K., Artemova E., Piontkovskaya I. SumTitles: a Summarization Dataset with Low Extractiveness, in: Proceedings of the 28th International Conference on Computational Linguistics., 2020. С. 5718-5730. 
Korablinov V., Braslavski P. RuBQ: A Russian Dataset for Question Answering over Wikidata, in: The Semantic Web – ISWC 2020: 19th International Semantic Web Conference, Athens, Greece, November 2–6, 2020, Proceedings.: Springer, 2020. С. 97-110. 
Efimov P., Chertok A., Leonid B., Braslavski P. SberQuAD – Russian Reading Comprehension Dataset: Description and Analysis, in: Experimental IR Meets Multilinguality, Multimodality, and Interaction.: Springer, 2020. С. 3-15. 
Ignatov D. I., Kwuida L. Interpretable Concept-Based Classification with Shapley Values, in: Ontologies and Concepts in Mind and Machine. 25th International Conference on Conceptual Structures, ICCS 2020.: Springer, 2020. С. 90-102. 
Ignatov D. I., Kwuida L. Shapley and Banzhaf Vectors of a Formal Concept, in: Proceedings of the Fifthteenth International Conference on Concept Lattices and Their Applications.: CEUR-WS.org, 2020. С. 259-271. 
Logacheva V., Teslenko D., Shelmanov A., Remus S., Ustalov D., Kutuzov A. B., Artemova E., Biemann C., Ponzetto S. P., Panchenko A. Word Sense Disambiguation for 158 Languages using Word Embeddings Only, in: Proceedings of The 12th Language Resources and Evaluation Conference.: European Language Resources Association (ELRA), 2020. С. 5943-5952. 
Shenbin I., Alekseev A., Tutubalina E., Malykh V., Nikolenko S. I. RecVAE: A new variational autoencoder for top-n recommendations with implicit feedback, in: WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining.: Association for Computing Machinery (ACM), 2020. С. 528-536. 
Kutuzov A., Fomin V., Mikhailov V., Rodina J. Shiftry: Web Service for Diachronic Analysis of Russian News, in: Computational Linguistics and Intellectual Technologies Papers from the Annual International Conference “Dialogue” (2020).: Изд-во РГГУ, 2020. С. 485-501. 
Shavrina T., Emelyanov A., Fenogenova A., Fomin V., Mikhailov V., Evlampiev A., Malykh V., Larin V., Natekin A., Vatulin A., Romov P., Anastasiev D., Zinov N., Chertok A. Humans Keep It One Hundred: an Overview of AI Journey, in: Proceedings of The 12th Language Resources and Evaluation Conference.: European Language Resources Association (ELRA), 2020. С. 2276-2284. 
Makarov I., Mikhail M., Kiselev D. Fusion of text and graph information for machine learning problems on networks // PeerJ Computer Science. 2021. Vol. 7. P. 1-26. doi
Tutubalina E., undefined., Мифтахутдинов З., Sakhovskiy A., Malykh V., Nikolenko S. I. The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews // Bioinformatics. 2021. Vol. 37. No. 2. P. 243-249. doi
Artemova E. Deep Learning for the Russian Language, in: The Palgrave Handbook of Digital Russia Studies.: Palgrave Macmillan, 2021. С. 465-481. 
Ahmed M. M. T., Delhibabu R. Cross-Domain Co-Author Recommendation Basedon Knowledge Graph Clustering, in: Intelligent Information and Database Systems. ACIIDS 2021.: Springer, 2021. 
Ignatov D. I., Kwuida L. On Interpretability and Similarity in Concept-Based Machine Learning, in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020. Revised Supplementary Proceedings.: Springer, 2021. 
Muratova A., Mitrofanova E., Islam R. Comparison of Machine Learning Methods for Life Trajectory Analysis in Demography, in: Intelligent Information and Database Systems. ACIIDS 2021.: Springer, 2021. С. 630-642. 
Ekaterina A. Deep Learning for the Russian Language, in: The Palgrave Handbook of Digital Russia Studies.: Palgrave Macmillan, 2021. С. 001-002. 
Klyuchnikov N., Trofimov I., Artemova E., Salnikov M., Fedorov M., Burnaev E. V. NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing / arXiv. Series arXiv:[cs.LG]. "arXiv:[cs.LG]". 2020.