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Efficient Semantic Structure Analysis of Korean Dialogue Sentences using an Active Learning Method  

Kim, Hark-Soo (강원대학교 컴퓨터정보통신공학)
Publication Information
Journal of KIISE:Software and Applications / v.35, no.5, 2008 , pp. 306-312 More about this Journal
Abstract
In a goal-oriented dialogue, speaker's intention can be approximated by a semantic structure that consists of a pair of a speech act and a concept sequence. Therefore, it is very important to correctly identify the semantic structure of an utterance for implementing an intelligent dialogue system. In this paper, we propose a model to efficiently analyze the semantic structures based on an active teaming method. To reduce the burdens of high-level linguistic analysis, the proposed model only uses morphological features and previous semantic structures as input features. To improve the precisions of semantic structure analysis, the proposed model adopts CRFs(Conditional Random Fields), which show high performances in natural language processing, as an underlying statistical model. In the experiments in a schedule arrangement domain, we found that the proposed model shows similar performances(92.4% in speech act analysis and 89.8% in concept sequence analysis) to the previous models although it uses about a third of training data.
Keywords
active learning; semantic structure; speech act; concept sequence;
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Times Cited By KSCI : 2  (Citation Analysis)
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