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.
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.
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.
Улучшение поиска локальных событий на основе сверточных квадродеревьев с помощью семантической фильтрации на основе данных Instagram
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.
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.
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