Title: Multilingual Sentiment Analysis
Authors: Přibáň, Pavel
Issue Date: 2020
Publisher: University of West Bohemia in Pilsen
Document type: zpráva
URI: http://hdl.handle.net/11025/42665
Keywords: zpracování přirozeného jazyka;analýza sentimentu;strojové učení;reprezentace textu
Keywords in different language: natural language processing;sentiment analysis;machine learning;text meaning representation
Abstract in different language: Natural language processing (NLP) became an essential part of the artificial in-telligence field that is used daily in industry and by millions of people. Sentimentanalysis as a part of NLP is no exception. Most of research in sentiment analysis hasbeen done primarily for English, creating a significant gap in performance betweenEnglish and other languages.In this thesis, we describe the fundamental theory behind sentiment analysis. Wesummarize tasks of sentiment analysis and tasks that are related to sentiment anal-ysis. Along with a description of common basic and initial approaches, we also coverrecent state-of-the-art techniques for sentiment analysis.We provide a detailed description of common machine learning techniques used forsentiment analysis and also very recent state-of-the-art machine learning methodsand architectures of neural networks and deep learning. Further, we describe cross-lingual approaches that allow a knowledge transfer between languages.In the end, we recap our preliminary work and future direction and the aims of thefinal doctoral thesis.
Rights: © University of West Bohemia in Pilsen
Appears in Collections:Zprávy / Reports (KIV)

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