Principle-based approach for semi-Automatic construction of a restaurant question answering system from limited datasets

Ting Hao Yang, Yu Lun Hsieh, Youshan Chung, Cheng Wei Shih, Shih Hung Liu, Yung Chun Chang, Wen Lian Hsu

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

1 Citation (Scopus)

Abstract

Question answering (QA) is an important research issue in natural language processing, and most state-of-the-Art question answering systems are based on statistical models. After wit nessing recent achievements in ArtfIcial Intelligent (Al), many businesses wish to apply those techniques to an automatic QA system that is capable of providing 24-hour customer services for their clients. However, o ne imminent problem is the lack of labeled training data for the specfIc domain. To address this issue, we propose to combine a knowledge-based approach and an automatic principle generation process to build a QA system from limited resources. Experiments conducted on a Mandarin Restaurant dataset show that our system achieves an average accuracy of 44% for 10 question types. It demonstrates that our approach can provide an effective tool when creating a QA system.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE 17th International Conference on Information Reuse and Integration, IRI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages520-524
Number of pages5
ISBN (Electronic)9781509032075
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event17th IEEE International Conference on Information Reuse and Integration, IRI 2016 - Pittsburgh, United States
Duration: Jul 28 2016Jul 30 2016

Conference

Conference17th IEEE International Conference on Information Reuse and Integration, IRI 2016
CountryUnited States
CityPittsburgh
Period7/28/167/30/16

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Keywords

  • Alignment
  • Dominating Set
  • Ontology

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

Cite this

Yang, T. H., Hsieh, Y. L., Chung, Y., Shih, C. W., Liu, S. H., Chang, Y. C., & Hsu, W. L. (2016). Principle-based approach for semi-Automatic construction of a restaurant question answering system from limited datasets. In Proceedings - 2016 IEEE 17th International Conference on Information Reuse and Integration, IRI 2016 (pp. 520-524). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IRI.2016.77