Research And Design Of Intelligent Recommended Ordering System Based On Spring Boot

People go to restaurants in most cases is currently in store by the waiter order and then wait for the waiter order to the kitchen.And after the meal,people choice the form of the code or cash payment.People through the traditional artificial order for some big restaurant not only in the form of efficiency is low,but place the order to the kitchen and dining to complete the checkout of artificial operation error rate is high.For consumers,the waiting time is long and the efficiency is low.And for the merchants,the order is cumbersome,the labor cost is high,the recurring billing statistics are inconvenient,and the feedback of the consumers can not be obtained in time.This article is based on the actual needs of a restaurant in Jinan during my internship.This article researches and designs the intelligent recommendation ordering system based on Spring Boot,and introduces the WeChat public platform with a large amount of users.The system is divided into consumer WeChat ordering system and merchant management system.In addition,the system will recommend the dishes that the consumer may be interested in through the recommendation algorithm according to the customer's previous meal rating in the restaurant.The system adopts the current popular development technology in design.Spring Boot is the core framework of the server side,which improves the development efficiency.In the front-end technology selection,select the Vue framework of the datadriven view and use Redis as the project cache database to make the page response smoother and faster.The use of the WebSocket protocol avoids the drawbacks of traditional real-time communication and improves the system performance.This article aims to meet the functional requirements of the ordering system for merchants and consumers.And from the aspects of improving consumer satisfaction,improving system development efficiency and improving system performance,etc,researching related technologies and theories,designing and implementing the intelligent recommendation ordering system based on Spring Boot.