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Ontology-Based Classifiers for Wikipedia Article Quality Classification

  • Kanchana Saengthongpattana
  • Thepchai Supnithi
  • Nuanwan SoonthornphisajEmail author
Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 807)

Abstract

Quality of Wikipedia article is the main issues that need to be solved. This research proposes the ontology-based classification framework that considers the quality of article in term of its comprehensive content which is one of the properties for featured and good articles in Thai Wikipedia. We create concepts or main ideas of articles in three domains using ontology as a knowledge representation. Knowledge based are created using OAM tool that do data mapping and classify the quality of articles via set of rules. We have investigated the ontology approach which combined Naïve Bayes classifier and found that the precision of our proposed method outperform traditional Naïve Bayes for two times.

Keywords

Ontology Thai Wikipedia Concept feature Naïve Bayes Classifier 
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Notes

Acknowledgements

This research is supported by Kasetsart University Research and Development. (KURDI). We would like to thank Language and Semantic Technology Laboratory, NECTEC for providing the platform for ontology development. Special thank goes to Dr. Marut Buranarach for his technical support.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kanchana Saengthongpattana
    • 1
    • 2
  • Thepchai Supnithi
    • 1
  • Nuanwan Soonthornphisaj
    • 2
    Email author
  1. 1.Language and Semantic Technology LaboratoryNational Electronics and Computer Technology Center (NECTEC)PathumthaniThailand
  2. 2.Department of Computer Science, Faculty of ScienceKasetsart UniversityBangkokThailand

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