Marina Ananyeva
- Doctoral Student:Faculty of Computer Science / School of Data Analysis and Artificial Intelligence
- Research Assistant:Faculty of Computer Science / Laboratory for Models and Methods of Computational Pragmatics
- Marina Ananyeva has been at HSE University since 2023.
Postgraduate Studies
4th year of study
Approved topic of thesis: Interpretable methods of recommender systems based on knowledge graphs and attention mechanism
Academic Supervisor: Ignatov, Dmitry I.
Courses (2022/2023)
- Recommender Systems (Master’s programme; Faculty of Computer Science; 2 year, 1 module)Rus
- Past Courses
Courses (2021/2022)
Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; field of study "38.03.01. Экономика", field of study "38.03.01. Экономика"; 3 year, 1, 2 module)Rus
- Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; 4 year, 1, 2 module)Rus
- Research Seminar (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Rus
Courses (2020/2021)
- Data Analysis in Economics and Finance (Bachelor’s programme; Faculty of World Economy and International Affairs; 3 year, 1 module)Eng
- Data Analysis in Politics and Journalism (Bachelor’s programme; Faculty of World Economy and International Affairs; 3 year, 1 module)Eng
Data Analysis in Python (Bachelor’s programme; Faculty of World Economy and International Affairs; field of study "41.03.05. Международные отношения", field of study "41.03.06. Публичная политика и социальные науки"; 2 year, 2-4 module)Eng
- Data Analysis in Python (Bachelor’s programme; Faculty of Economic Sciences; 2 year, 1, 2 module)Rus
- Research Seminar (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Rus
Courses (2019/2020)
- Data Analysis and Visualization (Bachelor’s programme; School of Foreign Languages; 2 year, 1, 2 module)Rus
- Data Science (Bachelor’s programme; Faculty of Economic Sciences; 2 year, 3, 4 module)Rus
Courses (2018/2019)
Publications11
- Chapter Makhneva E., Sverkunova A., Lashinin O., Ananyeva M., Kolesnikov S. Make your next item recommendation model time sensitive, in: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery (ACM), 2023. doi P. 191-195. doi
- Chapter Romanov A., Lashinin O., Ananyeva M., Kolesnikov S. Time-Aware Item Weighting for the Next Basket Recommendations, in: RecSys '23: Proceedings of the 17th ACM Conference on Recommender Systems. Association for Computing Machinery (ACM), 2023. doi P. 985-992. doi
- Chapter Наумов С., Ananyeva M., Лашинин О. А., Колесников С. С., Ignatov D. I. Time-Dependent Next-Basket Recommendations, in: Advances in Information Retrieval. 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2–6, 2023, Proceedings, Part II. Springer, 2023. doi doi
- Article Красильников Д. И., Лашинин О. А., Цыганков М. Р., Ananyeva M., Колесников С. С. Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations // CEUR Workshop Proceedings. 2023. P. 1-10.
- Article Лашинин О. А., Ananyeva M. Next-Basket Recommendation Constrained by Total Cost // CEUR Workshop Proceedings. 2022. P. 1-4.
- Article Ananyeva M., Лашинин О. А., Кузнецова М. Е. Revisiting the performance evaluation of knowledge-aware recommender systems: are we making progress? // CEUR Workshop Proceedings. 2022. P. 1-7.
- Article Ananyeva M., Лашинин О. А., Иванова В. В., Колесников С. С., Ignatov D. I. Towards interaction-based user embeddings in sequential recommender models // CEUR Workshop Proceedings. 2022. P. 1-9.
- Chapter Ananyeva M., Makarov I., Pendiukhov M. GSM: Inductive Learning on Dynamic Graph Embeddings, in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics. Springer, 2020. doi P. 85-99. doi
- Chapter Laptsuev Rodion, Ananyeva Marina, Meinster Dmitry, Karpov I., Makarov I., Zhukov L. E. Information Propagation Strategies in Online Social Networks, in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics Vol. 247. Springer, 2018. doi P. 319-328. doi
- Article Kurmukov A., Ananyeva M., Dodonova Y., Zhukov L. E. Classifying Phenotypes Based on the Community Structure of Human Brain Networks // Lecture Notes in Computer Science. 2017. P. 3-11. doi (in press)
- Article Ананьева М. Е., Курмуков А. И., Додонова Ю. А., Жуков Л. Е., Гутман Б., Фасковиц Дж., Джаханшад Н., Томпсон П. Оценивание сходства разбиений графов на пересекающиеся сообщества // Сборник трудов 41-й междисциплинарной школы-конференции ИППИ РАН "Информационные технологии и системы 2017". 2017. С. 7-15. (in press)
Conferences
- 2022
16th ACM Conference on Recommender Systems (RecSys). 4th Workshop of Knowledge-aware and Conversational Recommender Systems (KaRS) (Сиэтл). Presentation: Revisiting the performance evaluation of knowledge-aware recommender systems: are we making progress?
16th ACM Conference on Recommender Systems (RecSys). 5th Workshop on Online Recommender Systems and User Modeling (ORSUM) (Сиэтл ). Presentation: Towards interaction-based user embeddings in sequential recommender models
- 16th ACM Conference on Recommender Systems (RecSys). 5th Workshop on Online Recommender Systems and User Modeling (ORSUM) (Сиэтл ). Presentation: Next-basket recommendation with flexible total cos
16th ACM Conference on Recommender Systems. The International Workshop on Personalization & Recommender Systems in Financial Services (FinRec) (Сиэтл). Presentation: Personal merchant recommendations in online banking