semantic analysis

In recent years, social media platforms have become powerful data collection tools to improve user experience. The vast amount of data generated through social media provides a unique opportunity to develop innovative recommendation systems. This article analyzes the application of data mining methods for social networks in the context of effective recommendation systems, focusing on three key methodologies: sentiment analysis (SA), topic modeling (TM) and social network analysis (SNA), highlighting their positive features.

The article is devoted to the use of semantic analysis in the generalization of text documents. The analysis of features of the most widespread methods of generalization of text documents and an estimation of quality of results of an estimation is carried out. Features of the improved method of annotative generalization of text documents, which uses the principles of hidden semantic analysis and elements of fuzzy logic to identify semantically important sentences, are presented.