APPLICATION OF SEMANTIC MODELS IN LITERARY STUDIES AND EXPERTISE OF COPYRIGHT OBJECTS

Abstract

The article examines the application of semantic models in the fields of copyright expertise and literary analysis. The content showcases various types of semantic models utilized for text analysis, such as Latent Semantic Analysis (LSA), topic modeling, named entity recognition (NER), sentiment analysis, and dependency parsing. While each model has its own advantages and drawbacks, challenges in their utilization exist, such as over-reliance on quantitative analysis, model biases, lack of contextual information, and potential misinterpretation of meaning. Nevertheless, semantic models have significantly impacted the field by enabling the identification of instances of plagiarism and copyright infringement more efficiently and accurately. The overview presented in the publication on the essence and peculiarities of using semantic models in copyright expertise and literary analysis allows for the following conclusions. Semantic models significantly improve the efficiency of text analysis. These models use advanced technologies to identify structural patterns, themes, and similar elements in texts, as well as allowing experts to gain a deeper understanding of the works they are analyzing. In the field of copyright expertise, semantic models are used for analyzing significant volumes of text and identifying possible copyright infringements. Although semantic models have many advantages, they also have functional limitations. It is important to be aware of these limitations and use analytical models in combination with other methods to ensure a more comprehensive understanding of the text. There are several ways to address possible problems with using semantic models, including combining quantitative and qualitative analysis, using multiple models at once, taking into account selection biases of analytical information, studying the broader context, and additional verification of results by human experts. Ultimately, the use of semantic models in copyright expertise and literary analysis has enormous practical value, but it is important to be aware of their limitations and use them in conjunction with other analysis methods to ensure the most objective and comprehensive research. As technology develops, new and more advanced semantic models will be developed that will allow for even more detailed analysis of texts.