Abstract
AbstractTo understand emotion and make machine emotion is one of the goals of affective computing. In order to recognize one’s intention from the communication, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion to describe inter-relationship of mental states is still full of challenges. In this paper, an emotion ontology from Chinese dictionary is semi-automatically created for human machine interaction. The proposed method of construction of emotion ontology includes affective word annotation and emotion predicate hierarchy extraction. Firstly, over 7,000 common affective words have been manually labeled as affective with their detailed explanations and been collected for an affective lexicon, then the consistent relationships in the affective lexicon are automatically parsed and a serial of emotion hierarchical structures are built up. More than 50 affective categories are extracted and about 5,000 nouns and adjectives, 2,000 verbs are categorized into the predicate hierarchy.KeywordsSentiment AnalysisBasic EmotionEmotion CategorySemantic RoleLexical KnowledgeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have