Answer segmentation for question answering using latent dirichlet allocation and delta Bayesian information criterion

Ming Hsiang Su, Tsung Hsien Yang, Wu Hsuan Lin, Chung Hsien Wu

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

This study presents an approach to answer segmentation for the question answering system in a closed domain: a message board for emotional comfort. In this study, the unstructured articles were collected from the psychological consultation websites. In unstructured document processing, supervised latent Dirichlet allocation (SLDA) is employed for event detection and SLDA with delta Bayesian Information Criterion (delta-BIC) are employed for answer segmentation. In this study, the proposed method is applied to the negative emotion event detection of a user to provide appropriate answers segmented by the proposed method from the unstructured documents. K-Fold cross validation was employed to compare the performance of the proposed method. The evaluation result shows that the precision and recall of the proposed method achieved 96.62% and 84.2% when the distance between the detected segmentation points to the correct segmentation point is 2. The encouraging results confirm the usability of this proposed method for future applications.

原文English
主出版物標題2016 International Conference on Orange Technologies, ICOT 2016
發行者Institute of Electrical and Electronics Engineers Inc.
頁面9-12
頁數4
ISBN(電子)9781538648315
DOIs
出版狀態Published - 2016 7月 2
事件2016 International Conference on Orange Technologies, ICOT 2016 - Melbourne, Australia
持續時間: 2016 12月 182016 12月 20

出版系列

名字2016 International Conference on Orange Technologies, ICOT 2016
2018-January

Other

Other2016 International Conference on Orange Technologies, ICOT 2016
國家/地區Australia
城市Melbourne
期間16-12-1816-12-20

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 電腦視覺和模式識別
  • 行為神經科學
  • 認知神經科學

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