Improving the Accuracy in Sentiment Classification in the Light of Modelling the Latent Semantic Relations

This paper presents the Methodology of Improving the Accuracy in Text Classification in Light of Modelling the Latent Semantic Relations (LSR). The aim of this Methodology to find the ways of eliminating the Limitations of Discriminant and Probabilistic methods for LSR revealing and customize the Text Classification Process to the more accurate recognition of the text tonality using the knowledge about the text's Hierarchical Semantic Context on the form of Corpora-based Hierarchical Sentiment Dictionary. The main scientific contributions of this research is the set of approaches to improve the qualitative characteristics of Text Classification process: combination of the Discriminant and Probabilistic methods allowing to decrease the influences the Limitations of these methods on the LSR revealing process; considering each document as a complex structure allowing estimate documents integrally by separated classification of topically completed textual component (paragraphs); taking into account the features of Argumentative type of documents (Reviews) allowing to use for development the Text Classification methodology the author's subjective evaluation of text tonality. Tonality, expressed by the document's author, has a significant, but not critical, effect on the qualitative indicators of Sentiment Recognition