An ingredient selection system for patients using SWRL rules optimization and food ontology

Abstract

This paper presents research on the design and development of an ontology to represent knowledge about food and nutrition for patients and on the development and optimization of SWRL (Semantic Web Rule Language) rules to select suitable ingredients for patients. Emphasis was placed on optimizing search response times by testing different rule processing approaches to achieve the fastest processing time. According to the effort on seeking the way to optimize SWRL inference rules for recommending the most appropriate ingredients to the patients, it was found that the particular rule pattern can be processed faster than the previous rules designed for the original structure at an average of 35 %.