DOI
10.34229/KCA2522-9664.25.3.1
UDC 004.8
3 Institute of Information Technologies and Systems, National Academy of Sciences of Ukraine, Kyiv, Ukraine
enasirov@gmail.com
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4 Institute of Information Technologies and Systems, National Academy of Sciences of Ukraine, Kyiv, Ukraine
taranukha@ukr.net
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COMPARATIVE ANALYSIS OF NEURAL MODELS
FOR TEXT CLASSIFICATION PROBLEMS
Abstract. The paper investigates the phenomenon of fake messages and approaches to their detection. A comparative analysis of the effectiveness of using different neural network models for the tasks of searching and classifying text fragments containing false messages is conducted. The influence of model’s dimension on the learning speed, detection accuracy, and ability to adapt to unknown data is investigated.
Keywords: artificial intelligence, computational linguistics, neural network.
full text
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