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http://dx.doi.org/10.5762/KAIS.2010.11.8.3021

A Machine Learning based Method for Measuring Inter-utterance Similarity for Example-based Chatbot  

Yang, Min-Chul (Department of Computer and Radio Communications Engineering, Korea University)
Lee, Yeon-Su (Department of Computer and Radio Communications Engineering, Korea University)
Rim, Hae-Chang (Division of Computer and Communications Engineering, Korea University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.11, no.8, 2010 , pp. 3021-3027 More about this Journal
Abstract
Example-based chatBot generates a response to user's utterance by searching the most similar utterance in a collection of dialogue examples. Though finding an appropriate example is very important as it is closely related to a response quality, few studies have reported regarding what features should be considered and how to use the features for similar utterance searching. In this paper, we propose a machine learning framework which uses various linguistic features. Experimental results show that simultaneously using both semantic features and lexical features significantly improves the performance, compared to conventional approaches, in terms of 1) the utilization of example database, 2) precision of example matching, and 3) the quality of responses.
Keywords
Dialogue system; Example-based chatbot;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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