Daubenschütz, Tim (2015) Using Textual Emotion Extraction in Context-Aware Computing. Bachelor thesis, Institute of Databases and Information Systems.
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Abstract
In 2016, the number of global smartphone users will surpass 2 billion. The common owner uses about 27 apps monthly. On average, users of SwiftKey, an alternative Android software keyboard, type approximately 1800 characters a day. Still, all of the user-generated data of these apps is, for the most part, unused by the owner itself. To change this, we conducted research in Context-Aware Computing, Natural Language Processing and Affective Computing. The goal was to create an environment for recording this non-used contextual data without losing its historical context and to create an algorithm that is able to extract emotions from text. Therefore, we are introducing Emotext, a textual emotion extraction algorithm that uses conceptnet5’s realworld knowledge for word-interpretation, as well as Cofra, a framework for recording contextual data with time-based versioning.
Item Type: | Thesis (Bachelor) |
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Subjects: | DBIS Research > Master and Phd-Thesis |
Divisions: | Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Master and Phd-Thesis |
Depositing User: | Herr Marc Schickler |
Date Deposited: | 13 May 2015 16:32 |
Last Modified: | 13 May 2015 16:32 |
URI: | http://dbis.eprints.uni-ulm.de/id/eprint/1151 |