As information and communication technology develops swiftly, amount of information produced by various sources grows as well. Sorting and obtaining knowledge from this data requires significant effort which is not ensured easily by a human, meaning machine processing is taking place. Acquiring emotion from text data is an interesting area of research and it’s going through considerable expansion while being used widely. Purpose of this thesis is to create a system for positive and negative emotion detection from text along with evaluation of its performance. System was created with Java programming language and it allows training with use of large amount of data (known as Big Data), exploiting Spark library. Thesis describes structure and handling text from database used as source of input data. Classificator model was created with use of Support Vector Machines and optimized by the n-grams method.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:242026 |
| Date | January 2016 |
| Creators | Musil, David |
| Contributors | Harár, Pavol, Povoda, Lukáš |
| Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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