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Intelligent analysis of opinions and moods using fuzzy logic model

Tregubov Artem Sergeevich  (postgraduate student, Novosibirsk national research state University)

Every day, the volume of data suitable for extracting information is growing exponentially. One of the easily accessible sources of such data can be considered social networks. This type of Internet resource has become an excellent platform for the exchange of views, experience and knowledge. This document presents a model based on the theory of fuzzy sets that describes the emotional component of natural language texts. The goal is to test the suitability of the presented model for the automated intellectual analysis of opinions and hidden emotions in the text.

Keywords:fuzzy sets, sentiment analysis, natural language processing, machine learning, subjectivity analysis, knowledge extraction, data analysis, support vector method, maximum entropy method, opinion mining
 

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Citation link:
Tregubov A. S. Intelligent analysis of opinions and moods using fuzzy logic model // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2019. -№12. -С. 96-99
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