An analyzing method for dining behavior of college students in canteen based on data mining
In order to gain a deeper understanding of students'dining needs,improve the operational efficiency and service quality of canteens,this study designed a method for analyzing student dining behavior in university canteens through big data fea-ture mining analysis technology.Firstly,this study collected student dining data through the Jinshuju.net platform,utilized big data analysis and data mining techniques to gain a deeper understanding of the dining behavior,preferences,and needs of college stu-dents,and used iiMedia tools to determine the relationship between dining frequency and dining behavior.After analysis,it was found that there is a correlation between student dining behavior in the cafeteria and meal costs,cafeteria distance,waiting time,sit-ting time,dish quality,dish variety,etc.,but the degree of correlation varies among different factors.Based on the analysis results,effective dining optimization plans can be developed to improve the dining standards of students.
big data feature miningcollege cafeteriadining behaviorsatisfaction
万方数据
