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A Type-2 FML-Based Fuzzy Ontology for Dietary Assessment

  • Chapter
On the Power of Fuzzy Markup Language

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 296))

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Abstract

Diabetes and cardiovascular diseases have gradually become one of the world’s top ten fatal causes of death for the past few years. As far as the diet is concerned, it is easy to find out how to eat healthily and which food is good for people on the Internet. The diet behavior is highly personalized and also associated with the culture and religion. In this chapter, the type-2 FML-based fuzzy ontology is introduced. Moreover, the food ontology and type-2 fuzzy dietary ontology are further applied to the dietary assessment. Additionally, with the technologies of the type-2 fuzzy sets and fuzzy inference approach based on FML, the dietary healthy level is obtained to give users a reference for their eating. Experimental results show that the proposed approach is feasible to evaluate the dietary healthy level for the collected meal records.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science and Information Engineering, National University of Tainan, Tainan, Taiwan

    Mei-Hui Wang, Chang-Shing Lee & Zhi-Wei Chen

  2. The Computational Intelligence Centre, School of Computer Science and Electronic Engineering, University of Essex, Essex, UK

    Hani Hagras

  3. Dept. of Nutritional Service, National Cheng Kung University Hospital, Tainan, Taiwan

    Su-E Kuo, Hui-Ching Kuo & Hui-Hua Cheng

Authors
  1. Mei-Hui Wang
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  2. Chang-Shing Lee
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  3. Zhi-Wei Chen
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  4. Hani Hagras
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  5. Su-E Kuo
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  6. Hui-Ching Kuo
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  7. Hui-Hua Cheng
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Corresponding author

Correspondence to Mei-Hui Wang .

Editor information

Editors and Affiliations

  1. , School of Industrial Engineering,, Eindhoven University of Technology, PO Box 513, Eindhoven, 5600 MB, Netherlands

    Giovanni Acampora

  2. , Dept. of Computer Science, University of Salerno, Via Ponte Don Melillo, Fisciano, 84084, Salerno, Italy

    Vincenzo Loia

  3. , Dept. of Computer Science and, National University of Tainan, Shu-lin St., Tainan, 70005, Taiwan R.O.C.

    Chang-Shing Lee

  4. , Dept. of Computer Science and, National University of Tainan, Tainan, 70005, Taiwan R.O.C.

    Mei-Hui Wang

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Wang, MH. et al. (2013). A Type-2 FML-Based Fuzzy Ontology for Dietary Assessment. In: Acampora, G., Loia, V., Lee, CS., Wang, MH. (eds) On the Power of Fuzzy Markup Language. Studies in Fuzziness and Soft Computing, vol 296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35488-5_9

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  • DOI: https://doi.org/10.1007/978-3-642-35488-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35487-8

  • Online ISBN: 978-3-642-35488-5

  • eBook Packages: EngineeringEngineering (R0)

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