Effective Data Mining in philology

Abstract

Machine learning and data mining are closely related, as both approaches are used to identify patterns in data, but have some key differences in methods and applications. Machine learning is one of the main tools for data mining. Machine learning algorithms make it possible to identify patterns in data without the need for prior knowledge of all the rules that govern this data. Machine learning provides the ability to automate the process of data analysis and make more accurate predictions, while data mining provides a structured process for extracting useful knowledge/patterns from this data. In general, data mining in philology opens up new opportunities for the study of textual data, allowing to automate the analysis of linguistic phenomena and quickly explore large volumes of literary and cultural texts. This makes possible a more accurate and quick study of language evolution, stylistic features, as well as the analysis of sociocultural phenomena through the lens of language.