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A Comparative Study on Optimal Feature Identification and Combination for Korean Dialogue Act Classification  

Kim, Min-Jeong (고려대학교 컴퓨터.전파통신공학과)
Park, Jae-Hyun (고려대학교 컴퓨터.전파통신공학과)
Kim, Sang-Bum (SK Telecom 검색사업팀)
Rim, Hae-Chang (고려대학교 컴퓨터.통신공학부)
Lee, Do-Gil (고려대학교 민족문화연구원)
Publication Information
Journal of KIISE:Software and Applications / v.35, no.11, 2008 , pp. 681-691 More about this Journal
Abstract
In this paper, we have evaluated and compared each feature and feature combinations necessary for statistical Korean dialogue act classification. We have implemented a Korean dialogue act classification system by using the Support Vector Machine method. The experimental results show that the POS bigram does not work well and the morpheme-POS pair and other features can be complementary to each other. In addition, a small number of features, which are selected by a feature selection technique such as chi-square, are enough to show steady performance of dialogue act classification. We also found that the last eojeol plays an important role in classifying an entire sentence, and that Korean characteristics such as free order and frequent subject ellipsis can affect the performance of dialogue act classification.
Keywords
Dialogue Act Classification; Korean Characteristics; feature identification;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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