A Novel recipes recommendation system Based on Knowledge-Graph
Bo Huang, Xiaonan Shi, Rongqiang Wang, Chenyang Wang, Yuanhao Han · 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP) · 2022
With the improvement of living standards, the demand for personalized recipes is getting more and more attention. Therefore, this paper designs and implements a beneficial recipe recommendation system based on dietary knowledge mapping. The front-end of the system uses Vue.js to build the user interface, and the back-end uses Spring MVC framework to implement. And the recommendation technology based on the knowledge graph is studied, and the recipe recommendation method is improved by using knowledge graph. Firstly, we crawled recipe knowledge through crawlers and built a dietary knowledge graph integrating multi-domain information by using the rich semantics of knowledge graph. Secondly, the knowledge graph is combined with the collaborative filtering algorithm implemented by Mahout to improve the effectiveness of recommendations. Finally, an intelligent Q&A module is developed for the system based on the knowledge graph to provide accurate and effective recipes for people and patients with dietary choice difficulties.