Top > JACIII > A Chronic Disease Diet Recommendation System Based on Domain O ...

single-jc.php

JACIII Vol.21 No.3 pp. 474-482
doi: 10.20965/jaciii.2017.p0474
(2017)

Paper:

Views over last 60 days: 1,768

A Chronic Disease Diet Recommendation System Based on Domain Ontology and Decision Tree

Rung-Ching Chen*, Chung-Yi Huang*,**, and Yu-Hsien Ting*

*Department of Information Management, Chaoyang University of Technology
168 Jifeng E. Rd., Wufeng District, Taichung 41349, Taiwan

**Library, Chienkuo Technology University
No.1, ChiehShou N. Rd., Changhua City 50094, Taiwan

Received:
March 28, 2016
Accepted:
January 4, 2017
Online released:
May 19, 2017
Published:
May 20, 2017
Creative Commons License
Keywords:
ontology, decision tree, chronic, nutrients, dietary recommendation
Abstract
As society develops and science and technology improve, people have come to care more about a healthy diet. Diet types have gradually changed and focused more on health management. Taiwan is becoming an aging society in which individuals have irregular lifestyles, long-term unhealthy diets, stressful work, and chronic diseases such as diabetes, hypertension, and high cholesterol. However, most dietary recommendation systems cannot give dietary recommendations for patients with chronic diseases. Though healthy foods are recommended, the systems contain little information on whether nutrients are in balance. Therefore, this study constructed a diet recommendation system for chronic diseases using expert knowledge, which enables more convenient and precise dietary recommendations for chronic diseases. In this study, we use an ontology, decision trees, and Jena to construct the recommendation system. The dietary recommendations results are evaluated by dietitians, and the verification accuracy is 100%. Therefore, this system of dietary recommendations can provide convenient, healthy, dietary recommendations for nutrients for patients with chronic diseases.
Cite this article as:
R. Chen, C. Huang, and Y. Ting, “A Chronic Disease Diet Recommendation System Based on Domain Ontology and Decision Tree,” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.3, pp. 474-482, 2017.
Data files:
References
  1. [1] United Nations, “World Population Ageing 2015 Report,” Available from: http://www.un.org/en/development/desa/popu-lation/publications/pdf/ageing/WPA2015_Report.pdf [AccessedNovember 4, 2016]
  2. [2] M. Svensson, K. Hook, and R. Coster, “Designing and evaluating kalas: A social navigation system for food recipes,” ACM Trans. Comput.-Hum. Interact., Vol.12, No.3, pp. 374-400, doi:10.1145/1096737.1096739, 2005.
  3. [3] T. R. Gruber, “A translation approach to portable ontology specifications,” Knowledge Acquisition, Vol.5, No.2, pp. 199-220, doi:http://dx.doi.org/10.1006/knac.1993.1008, 1993.
  4. [4] M. Ueda, M. Takahata, and S. Nakajima, “User’s food preference extraction for personalized cooking recipe recommendation,” Proc. of the second Workshop on Semantic Personalized Information Management: Retrieval and Recommendation, Bonn, Germany. pp. 98-105, 2011.
  5. [5] R. C. Chen and Y. D. Lin, “The Recommendation of Diet for Chronic Diseases Based on Knapsack Problem and Domain Ontology,” Int. J. of Advanced Information Technologies, Vol.6, No.2, pp. 155-167, 2013.
  6. [6] G. Geleijnse, P. Nachtigall, P. v. Kaam, and L. Wijgergangs, “A personalized recipe advice system to promote healthful choices,” The 16th Int. Conf. on Intelligent user interfaces, pp. 437-438, 2011.
  7. [7] C. M. Hu, “A Nutrition Analysis System based on Recipe Ontology,” Master Thesis, University of Taipei Medical, 2006.
  8. [8] Q. l. Guo and M. Zhang, “Semantic information integration and question answering based on pervasive agent ontology,” Expert Systems with Applications, Vol.36, No.6, pp. 10068-10077, 2009.
  9. [9] C. J. Thomas, “Just What Is an Ontology, Anyway?,” IT Professional, Vol.11, No.5, pp. 22-27, 2009.
  10. [10] Y. Labrou and T. Finin, “Yahoo! as an ontology: using Yahoo! categories to describe documents,” The eighth Int. on Information and knowledge management, pp. 180-187, 1999.
  11. [11] D. L. McGuinness and F. v. Harmelen, “OWL Web Ontology Language Overview,” Available from:
    https://www.w3.org/TR/owl-features/ [Accessed March 27, 2016]
  12. [12] T. Gruber, “What is an Ontology?,” Available from: http://ejournal.narotama.ac.id/files/Ontology.pdf, The original URL: http://www-ksl.stanford.edu/kst/what-is-an-ontology.html
    [Accessed June 11, 2016]
  13. [13] Wikipedia, “Ontology (information science),” Available from: https://en.wikipedia.org/wiki/Ontology_(information_science)
    [Accessed March 27, 2016]
  14. [14] J. R. Quinlan, “C4.5: programs for machine learning,” Elsevier, 2014.
  15. [15] J. R. Quinlan, “Improved use of continuous attributes in C4.5,” J. of artificial intelligence research, Vol.4, pp. 77-90, 1996.
  16. [16] Wikipedia, “ID3 algorithm,” Available from:
    https://en.wikipedia.org/wiki/ID3_algorithm
    [Accessed November 4, 2016]
  17. [17] Wikipedia, “C4.5 algorithm,” Available from:
    https://en.wikipedia.org/wiki/C4.5_algorithm
    [Accessed March 27, 2016]
  18. [18] Wikipedia, “Entropy (information theory),” Available from:
    https://en.wikipedia.org/wiki/Entropy_(information_theory)
    [Accessed March 27, 2016]
  19. [19] Wikipedia, “Jena (framework),” Available from:
    https://en.wikipedia.org/wiki/Jena_(framework)
    [Accessed March 27, 2016]
  20. [20] Wikipedia, “Body mass index,” Available from:
    https://en.wikipedia.org/wiki/Body_mass_index
    [Accessed March 27, 2016]
  21. [21] Mackay Memorial Hospital, “How to calculate the ideal body weight and calorie needs,” Available from:
    http://www.mmh.org.tw/nutrition/ibw_doc.htm
    [Accessed June 12, 2016]
  22. [22] Wikipedia, “Waist-hip ratio,” Available from:
    https://en.wikipedia.org/wiki/Waist-hip_ratio
    [Accessed June 11, 2016]
  23. [23] Food and Drug Administration Ministry of Health and Welfare, “Daily Dietary Guidelines,” Food and Drug Administration, Ministry of Health and Welfare, 2012.
  24. [24] Taichung Hospital, Ministry of Health and Welfare, “Diabetic diet principles,” Available from:
    http://www.taic.mohw.gov.tw/?aid=509&pid=99&page_name=deta il&type=928&iid=1601 [Accessed June 11, 2016]
  25. [25] Health Promotion Administration, Ministry of Health and Welfare, “High cholesterol,” Available from:
    http://www.hpa.gov.tw/BHPNet/Portal/file/ThemeULFile/2007082 0300000004/0001.pdf [Accessed June 11, 2016]
  26. [26] Food and Drug Administration, Ministry of Health and Welfare, “Taiwan food nutrition database,” Available from:
    https://consumer.fda.gov.tw/FoodAnalysis/ingredients.htm
    [Accessed March 27, 2016]
  27. [27] Wikipedia, “Information gain in decision trees,” Available from: https://en.wikipedia.org/wiki/Information_gain_in_decision_trees
    [Accessed November 4, 2016]
  28. [28] The Apache Software Foundation, “Reasoners and rule engines: Jena inference support,” Available from:
    http://jena.apache.org/documentation/inference/
    [Accessed March 27, 2016]
  29. [29] R. H. Eckel et al., “2013 AHA/ACC Guideline on Lifestyle Management to Reduce Cardiovascular Risk: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines,” J. of the American College of Cardiology, Vol.63, No.25_PA, 2014.

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Oct. 01, 2024