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Intelligent Recommendation and Process Generation Technology for Smart Restaurant Scenarios Based on Knowledge Graph

Author(s)

Zhanqiang Liu1, Liang Dong2, Jianling Zhao1,*, Jianguo Wang3

Affiliation(s)

1Shandong Hehe Information Technology Co., Ltd., Jinan, China 2Jinan BOSAI Network Technology Co., Ltd., Jinan, China 3Shandong Tongyun Network Technology Co., Ltd., Jinan, China *Corresponding Author

Abstract

In an effort to refine dish recommendation personalization and automate service procedures in smart restaurants, a graph system is engineered. This system consolidates knowledge from diverse sources, including dishes, raw materials, customer preferences, and operational sequences. The study then examines the dish recommendation approach and the process generation mechanism via graph reasoning.This paper investigates the joint recommendation strategy via graph embedding and path confidence, and incorporates a directed operation graph for the automated generation and dissemination of task instructions.The empirical evidence indicates that the method excels in recommendation accuracy, response delay, and process completion rate, along with commendable semantic interpretability and system stability.The study finds that the method exhibits superior performance in recommendation accuracy, response delay, and process completion rate, along with commendable semantic interpretability and system stability.

Keywords

Smart Restaurant; Knowledge Graph; Dish Recommendation; Process Generation

References

[1]Sha, F., Ding, C., Zheng, X., Wang, J., & Tao, Y. (2025). Weathering the Policy Storm: How Trade Uncertainty Shapes Firm Financial Performance through Innovation and Operations. International Review of Economics & Finance, 104274. [2]Sha, F., Meng, J., Zheng, X., & Jiang, Y. (2025). Sustainability Under Fire: How China-US Tensions Impact Corporate ESG Performance?. Finance Research Letters, 107882. [3]Zhang, L., & Meng, Q. (2025). User Portrait-Driven Smart Home Device Deployment Optimization and Spatial Interaction Design.