Original title: Algorithm for Detection of Positive and Negative Text
Authors: Musil, David
Document type: Papers
Language: cze
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: In the present, obtaining and sorting knowledge from data produced by various sources requires significant effort which is not ensured easily by a human, meaning machine processing is taking place. Purpose of this work was to create a system capable of positive and negative emotion detection from text along with evaluation of its performance. System allows training with use of large amount of data (known as Big Data), exploiting Spark library. Classificator model was created with use of Support Vector Machines. Highest achieved accuracy is 78,05% for Czech, 79,73% for German and 91,88% for English.
Keywords: artificial intelligence; Big Data; emotion detection; text-mining
Host item entry: Proceedings of the 22nd Conference STUDENT EEICT 2016, ISBN 978-80-214-5350-0

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/83904

Permalink: http://www.nusl.cz/ntk/nusl-383622


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers