Text processing with neural network in the direction of authorship

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The article deals with the task of text processing using neural networks to determine authorship. The relevance of this topic is due to the increasing role of artificial intelligence in various fields, including natural language processing. A practical example of implementation of neural network approach to text authorship determination using Keras Python library on Google Colaboratory platform is presented. The steps of data preparation, creation of training and test samples, model building and training are described. The obtained results demonstrate high accuracy of text authorship identification, reaching 95-98%.

Neural network, authorship, processing, data, text

Короткий адрес: https://sciup.org/170205085

IDR: 170205085   |   DOI: 10.24412/2500-1000-2024-5-1-249-253

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