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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2016 International Conference on Orange Technologies, ICOT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9-12
Number of pages4
Volume2018-January
ISBN (Electronic)9781538648315
DOIs
Publication statusPublished - 2018 Feb 1
Event2016 International Conference on Orange Technologies, ICOT 2016 - Melbourne, Australia
Duration: 2016 Dec 182016 Dec 20

Other

Other2016 International Conference on Orange Technologies, ICOT 2016
CountryAustralia
CityMelbourne
Period16-12-1816-12-20

Fingerprint

Websites
Processing
Emotions
Referral and Consultation
Psychology

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Behavioral Neuroscience
  • Cognitive Neuroscience

Cite this

Su, M. H., Yang, T. H., Lin, W. H., & Wu, C-H. (2018). Answer segmentation for question answering using latent dirichlet allocation and delta Bayesian information criterion. In 2016 International Conference on Orange Technologies, ICOT 2016 (Vol. 2018-January, pp. 9-12). [8278967] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOT.2016.8278967
Su, Ming Hsiang ; Yang, Tsung Hsien ; Lin, Wu Hsuan ; Wu, Chung-Hsien. / Answer segmentation for question answering using latent dirichlet allocation and delta Bayesian information criterion. 2016 International Conference on Orange Technologies, ICOT 2016. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 9-12
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Su, MH, Yang, TH, Lin, WH & Wu, C-H 2018, Answer segmentation for question answering using latent dirichlet allocation and delta Bayesian information criterion. in 2016 International Conference on Orange Technologies, ICOT 2016. vol. 2018-January, 8278967, Institute of Electrical and Electronics Engineers Inc., pp. 9-12, 2016 International Conference on Orange Technologies, ICOT 2016, Melbourne, Australia, 16-12-18. https://doi.org/10.1109/ICOT.2016.8278967

Answer segmentation for question answering using latent dirichlet allocation and delta Bayesian information criterion. / Su, Ming Hsiang; Yang, Tsung Hsien; Lin, Wu Hsuan; Wu, Chung-Hsien.

2016 International Conference on Orange Technologies, ICOT 2016. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 9-12 8278967.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Su MH, Yang TH, Lin WH, Wu C-H. Answer segmentation for question answering using latent dirichlet allocation and delta Bayesian information criterion. In 2016 International Conference on Orange Technologies, ICOT 2016. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 9-12. 8278967 https://doi.org/10.1109/ICOT.2016.8278967