Intelligent System for Automatic Selection of Sauces for Various Dishes Based on Ontology and Logical Inference
DOI:
https://doi.org/10.52575/2712-746X-2024-51-1-169-177Keywords:
intelligent system, recommendation, sauce, ontology, logical conclusion, culinary art, algorithm, semantic web, integration, ruby, javaAbstract
The article discusses the development of an intelligent system for automaticselection of sauces for various dishes using ontology and logical inference. The system aids in identifying the most suitable sauce based on dish type and culinary culture. It emphasizes the use of semantic web technologies and logical programming for accurate recommendations. Examples of dishes and sauces are provided, along with selection rules. The system's technical implementation includes RDF format for structured data representation and integration into everyday life using Ruby and Java for client and server parts, respectively. It highlights the system's adaptability for various culinary needs and development prospects. Additionally, the article focuses on the importance of integrating such a system into mobile and web applications for broader accessibility. It discusses the potential for use in the restaurant business to improve service quality and customer satisfaction. Future enhancements involve integrating with artificial intelligence systems for deeper analysis of user preferences and recommendation adaptations, covering both technical aspects and practical application in real-life scenarios.
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Иванов А.Б., Петров В.С. 2019. Развитие интеллектуальных систем в ресторанном бизнесе. Инженерный вестник Дона, 22(3), 156–162.
Смирнова Е.В. 2020. Применение онтологий для улучшения качества обслуживания в ресторанах. Инженерный вестник Дона, 23(1), 88–95.
Fernandez M., Lopez V. 2022. Enhancing Food Experience with AI-Driven Sauce Pairing. Journal of Culinary Science & Technology. DOI: 10.1080/15428052.2022.1654307.https://www.tandfonline.com/doi/abs/10.1080/15428052.2022.1654307
Gupta S., Khan M. 2019. Application of Logic Programming in Food Recipe Recommendation. Journal of Applied Logic, 35, 73–81.
Liu H., Lee C. 2020. Developing a Smart Sauce Recommendation System Using Machine Learning. International Journal of Gastronomy and Food Science, 17, 82–89.
Lopez V., Gómez-Pérez A. 2018. Advances in Ontology-Based Logical Data Processing. Journal of Web Semantics, 13(3), 45–60.
Patel R.K., Kumar S. 2019. Semantic Web Technologies in Intelligent Food Recommendation Systems. International Journal of Computer Science, 24(4), 234–241.
Smith J., Brown A. 2020. Ontology-Based Data Integration in Culinary Arts. Journal of Food Technology and Science, 15(2), 112–119.
Thompson R., Davis H. 2021. Use of Ontologies in Creating Interactive Culinary Systems. Journal of Computer and System Sciences, 62(1), 97–103. DOI: 10.1016/j.jcss.2020.05.007. https://www.sciencedirect.com/science/article/pii/S002200002030067X
Zhang Y., Wang X. 2021. Artificial Intelligence in the Food Industry: A Review. Journal of Food Science and Technology, 58(1), 39–49.
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