TY - GEN
T1 - Emotion ontology construction from Chinese knowledge
AU - Jiang, Peilin
AU - Wang, Fei
AU - Ren, Fuji
AU - Zheng, Nanning
PY - 2012
Y1 - 2012
N2 - To 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.
AB - To 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.
UR - https://www.scopus.com/pages/publications/84863382088
U2 - 10.1007/978-3-642-28604-9_49
DO - 10.1007/978-3-642-28604-9_49
M3 - 会议稿件
AN - SCOPUS:84863382088
SN - 9783642286032
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 603
EP - 614
BT - Computational Linguistics and Intelligent Text Processing - 13th International Conference, CICLing 2012, Proceedings
T2 - 13th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2012
Y2 - 11 March 2012 through 17 March 2012
ER -