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.. doi: 10.3390/smartcities7050107
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.. doi: 10.1145/3638530.3664187
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.. doi: 10.1016/j.procs.2023.12.004
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.. doi: 10.1109/CEC53210.2023.10254069
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.. doi: 10.1016/j.procs.2023.12.014
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.. doi: 10.1016/j.procs.2022.11.016
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.. doi: 10.1016/j.procs.2022.11.015
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.. doi: 10.1016/j.procs.2022.11.025
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.. doi: 10.1016/j.procs.2021.10.006
Российская Федерация, Санкт-Петербург