In this paper we present a semantic analyzer for aiding emotion recognition in Chinese. The analyzer uses a decision tree to assign semantic dependency relations between headwords and modifiers. It is able to achieve an accuracy of 83.5%. The semantic information is combined with rules for Chinese verbs containing emotion to describe the emotion of the people in the sentence. The rules give information on how to assign emotion to agents, receivers, etc. depending on the verb in the sentence. © Springer-Verlag Berlin Heidelberg 2006.
Yan, J., Bracewell, D. B., Ren, F., & Kuroiwa, S. (2006). A semantic analyzer for aiding emotion recognition in Chinese. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4114 LNAI-II, pp. 893–901). Springer Verlag. https://doi.org/10.1007/11816171_112