Filatova A., Perov I., Timoschak E., Batalenkov S., Kovalchuk M., Nasonov D. Advancing Project Management: Integrating Material Delivery in Multi-Contractor Multi-Mode RCPSP. GECCO 2024 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2024. pp. 1724-1727.
Kovalchuk M.A., Filatova A., Korneev A., Koreneva M., Nasonov D., Voskresenskii A., Boukhanovsky A. SemConvTree: semantic convolutional quadtrees for multi-scale event detection in Smart City. Smart Cities. 2024. Vol. 7. No. 5. pp. 2763-2780.
Voskresenskii A., Kovalchuk M., Filatova A., Nasonov D., Lutsenko A. Hybrid Algorithm for Multi-Contractor, Multi-Resource Project Scheduling in the Industrial Field. Procedia Computer Science. 2023. Vol. 229. pp. 28-38.
Filatova A., Kovalchuk M., Batalenkov S., Voskresenskiy A., Deeva I., Kalyuzhnaya A., Shpilman A., Kondrashova N., Dudnichenko M., Nasonov D. A Multi-Contractor Approach for MLRCPSP with the Graph Structure Optimization. IEEE Congress on Evolutionary Computation, CEC 2023. 2023. pp. 1-8.
Sergeeva J., Filatova A., Nasonov D., Lutsenko A. ClarTM: a method for geolocations clarification within extensive urban sites using topic modelling. Procedia Computer Science. 2023. Vol. 229. pp. 128-137.
Panov V., Kovalchuk M., Filatova A., Teryoshkin S. MuCAAT: Multilingual Contextualized Authorship Anonymization of Texts from social networks. Procedia Computer Science. 2022. Vol. 212. pp. 322-329.
Sergeeva J., Filatova A., Kovalchuk M., Teryoshkin S. SemAGR: semantic method for accurate geolocations reconstruction within extensive urban sites. Procedia Computer Science. 2022. Vol. 212. pp. 409-417.
Улучшение поиска локальных событий на основе сверточных квадродеревьев с помощью семантической фильтрации на основе данных Instagram
Korneev A., Kovalchuk M., Filatova A., Tereshkin S. Towards comparable event detection approaches development in social media. Procedia Computer Science. 2022. Vol. 212. pp. 312-321.
Filatova A., Nasonov D. SeSAM: semi-automated semantic analysis method of urban areas’ events with extreme levels of popularity based on public open data. Procedia Computer Science. 2021. Vol. 193. pp. 52-61.
Российская Федерация, Санкт-Петербург