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Título:
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Comparing the performance of knowledge-based and machine-learning approaches for the detection of emotions in an english Text
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Autor/a:
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Barnes, Jeremy
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Abstract:
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Treball de fi de màster en Lingüística Teòrica i Aplicada |
Abstract:
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Tutors: Juan María Garrido Almiñana i Antoni Badia i Cardús |
Abstract:
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The detection of emotion and sentiment analysis are very hot topics at the moment and the detection of emotion from written text still remains a difficult subject of this area of research. The main approaches to this task are knowledge-based approaches and machine-learning approaches. This paper examines the performance of two approaches (a knowledge-based and a machine-learning approach) on a small corpus of chat text annotated with emotion labels. It will be shown that the machine-learning approach used in this experiment outperforms the knowledge-based approach in all aspects. |
Materia(s):
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-Ensenyament assistit per ordinador -Llenguatge i emocions -Adquisició del coneixement (Sistemes experts) -Tractament del llenguatge natural (Informàtica) |
Derechos:
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Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Tipo de documento:
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Trabajo fin de máster |
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