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Sentiment Analysis of User-Generated Online Content

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dc.contributor.author BOBICEV, V.
dc.contributor.author SOKOLOVA, M.
dc.date.accessioned 2019-07-17T07:33:36Z
dc.date.available 2019-07-17T07:33:36Z
dc.date.issued 2015
dc.identifier.citation BOBICEV, V. SOKOLOVA, M. Sentiment Analysis of User-Generated Online Content. In: Telecomunicaţii, Electronică şi Informatică: proc. of the 5th intern. conf., May 20-23, 2015. Chişinău, 2015, pp. 335-338. ISBN 978-9975-45-377-6. en_US
dc.identifier.isbn 978-9975-45-377-6
dc.identifier.uri http://repository.utm.md/handle/5014/3585
dc.description.abstract This paper presents several experiments in the domain of automate text sentiment analysis. Comparison between machine learning (ML) and rule-based algorithms demonstrated that well-tuned rule-based methods obtain better results than general ML methods and it is necessary to use various types of features for obtaining satisfactory accuracy using ML algorithms. en_US
dc.language.iso en en_US
dc.publisher Technical University of Moldova en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject natural language en_US
dc.subject text analysis en_US
dc.subject text sentiment analysis en_US
dc.subject semantic lexicon en_US
dc.subject machine learning en_US
dc.subject limbaj natural en_US
dc.subject analiza textului en_US
dc.subject sentimente en_US
dc.subject lexicon semantic en_US
dc.subject învățarea mașinilor en_US
dc.title Sentiment Analysis of User-Generated Online Content en_US
dc.type Article en_US


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