糖尿病食物推荐的本体与语义匹配

2013 International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2013-12-02 DOI:10.1109/ICITEED.2013.6676233

Achmad Arwan, Bayu Priyambadha, R. Sarno, Mohamad Sidiq, H. Kristianto

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引用次数: 26

摘要

糖尿病患者的饮食建议对于控制血糖水平是必不可少的。目前，食物的准备是由营养专家完成的。患者对营养专家的依赖程度很高，无法独立选择食物。解决这些问题需要自动化系统来确定糖尿病患者的食物组合。在本研究中，设计并实现了自动化系统。本研究使用的技术是OWL和SWRL。利用OWL和SWRL技术探索糖尿病患者食物推荐自动化过程的研究很少。食品成分的自动处理需要基于本体的领域知识。但是，仅仅使用SWRL和OWL技术是不够的，因为需要单词的准确性。采用加权树相似度方法，引入语义本体理解，明确糖尿病患者的食物组成。73%的数据能被正确预测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Ontology and semantic matching for diabetic food recommendations

Foods recommendation for diabetes patients is indispensable for controlling blood sugar levels. Currently, the foods preparation is done by a nutrition expert. The patient's dependence on the nutrition experts is very high, thus the selection of foods could not be done independently. The Automation system to determine foods combination for diabetic patients is needed to solve these problems. In this study, the automation system has been designed and implemented. The technologies used in this research are the OWL and SWRL. There are few researches that explore an automation process of foods recommendation for diabetes patients using the technology of OWL and SWRL. Domain knowledge based on Ontology is needed to process foods composition automatically. However, using SWRL and OWL technology is not enough, because the accuracy of the words required. A semantic ontology understanding was added using weighted tree similarity method to specify the composition of foods for diabetic patients. 73% data were able to be correctly predicted by this method.

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2013 International Conference on Information Technology and Electrical Engineering (ICITEE)

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