Персона: Климов, Валентин Вячеславович
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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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- ПубликацияТолько метаданныеIntelligent Processing of Natural Language Search Queries Using Semantic Mapping for User Intention Extracting(2019) Chernyshov, A.; Balandina, A.; Klimov, V.; Климов, Валентин Вячеславович© 2019, Springer Nature Switzerland AG. Nowadays the leading world scientists and engineers center their attention to data mining and machine learning algorithms optimization and acceleration rather than inventing new ones. The natural language processing methods and tools are widely in use in production in the area of machine translation. The researches in the area of search engines and semantic search are mostly concentrated on data storage and further analysis. The majority of search engines use the huge amounts of previously accumulated user requests for predicting the search output without taking in attention this user intention by qualitative processing the request. In this paper we explore the idea of usage the semantic cognitive spaces for extracting the exact user intentions by analysis the natural language input requests. The final goal of our research is to develop a valid search query model for further usage in semantic search engines.
- ПубликацияОткрытый доступApplication of Long-Short Memory Neural Networks in Semantic Search Engines Development(2020) Klimov, V.; Balandina, A.; Chernyshov, A.; Климов, Валентин Вячеславович; Баландина, Анита Ивановна; Чернышов, Артем Андреевич© 2020 The Authors. Published by Elsevier B.V.This article provides an overview and description of the long-short memory approaches for the neural networks modelling and development. The authors show the possible application of these models and methods and consider its usage during the process of natural language understanding as the part of the semantic search system.
- ПубликацияОткрытый доступThe Application of Transformer Model Architecture for the Dependency Parsing Task(2021) Chernyshov, A.; Klimov, V.; Balandina, A.; Shchukin, B.; Чернышов, Артем Андреевич; Климов, Валентин Вячеславович; Баландина, Анита Ивановна; Щукин, Борис Алексеевич© 2020 Elsevier B.V.. All rights reserved.In this paper, authors discover the advantages of the attention-based neural network application to the natural language dependency-parsing task. The authors explain the architecture and show the results of comparison between attention-based neural network and long-short memory neural networks in relation to the dependency-parsing task.
- ПубликацияТолько метаданныеOverview of Natural Language Processing Approaches in Modern Search Engines(2020) Chernyshov, A.; Balandina, A.; Klimov, V.; Чернышов, Артем Андреевич; Баландина, Анита Ивановна; Климов, Валентин Вячеславович© 2020, Springer Nature Switzerland AG.This article provides an overview of modern natural language processing and understanding methods. All the monitored technologies are covered in the context of search engines. The authors do not consider any particular implementations of the search engines; however take in consideration some scientific research to show natural language processing techniques application prospects in the informational search industry.