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Advances in Computer Communication and Computational Sciences pp 521–533Cite as

Ontology-Based Natural Language Processing for Thai Herbs and Thai Traditional Medicine Recommendation System Supporting Health Care and Treatments (THMRS)

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 924))

Abstract

Herbs become increasingly popular in health care and treatments these days, because they are safe under careful usages. Although Thai herbs information can be retrieved from many websites, it takes long searching times for discovering the information that matches with users’ requirements. Therefore, this research aimed to develop a Thai herbs and Thai traditional medicines recommendation system for health care and treatments using ontology-based natural language processing (THMRS). In addition, users can use the proposed recommendation system via web or Windows application. The proposed THMRS is composed of ontology-based databases called Thaiherb, searching process using natural language combined with word tokenization and spell checking by ISG (Index of Similarity Group) Algorithm, translation from natural language to SPARQL commands is designed for semantic search, and the decision making whether information found will be delivered to users is done by co-occurrence density analysis. The search result was displayed in a single website or a window which is fast and user-friendly. The experiments show that the average F-Measure is 95.07%, the average precision is 93.76%, and the average recall is 96.42% which indicate that THMRS is very high efficiency.

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Author information

Authors and Affiliations

  1. Department of Applied Science, Faculty of Science and Technology, Nakhon Sawan Rajabhat University, Nakhon Sawan, Thailand

    Akkasit Sittisaman & Naruepon Panawong

Authors
  1. Akkasit Sittisaman
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  2. Naruepon Panawong
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Corresponding author

Correspondence to Naruepon Panawong .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Missouri–St. Louis, St. Louis, MO, USA

    Sanjiv K. Bhatia

  2. CSED, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India

    Krishn K. Mishra

  4. Department of Information Technology, Rajkiya Engineering College, Azamgarh, Uttar Pradesh, India

    Munesh C. Trivedi

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Sittisaman, A., Panawong, N. (2019). Ontology-Based Natural Language Processing for Thai Herbs and Thai Traditional Medicine Recommendation System Supporting Health Care and Treatments (THMRS). In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 924. Springer, Singapore. https://doi.org/10.1007/978-981-13-6861-5_45

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