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Comparing the performance of knowledge-based and machine-learning approaches for the detection of emotions in an english Text
Barnes, Jeremy
Treball de fi de màster en Lingüística Teòrica i Aplicada
Tutors: Juan María Garrido Almiñana i Antoni Badia i Cardús
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.
Ensenyament assistit per ordinador
Llenguatge i emocions
Adquisició del coneixement (Sistemes experts)
Tractament del llenguatge natural (Informàtica)
Attribution-NonCommercial-NoDerivs 3.0 Spain

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