Research of semantic text analysis methods and models

Abstract

This work provides a comprehensive review and evaluation of existing techniques for semantic text analysis. It explores a wide range of methodologies, including Bag-of-Words, TF-IDF, various word embedding models, semantic analysis techniques, sentiment analysis, and others. The analysis delves into the strengths, limitations, and applications of each method, highlighting their effectiveness in capturing semantic relationships and extracting meaningful insights from textual data. This work aims to provide valuable insights to inform the selection and implementation of semantic text analysis techniques, thus advancing the field of natural language processing.