Association analysis of dishes in Catering Enterprise
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Author(s)
Abstract
This article implement Python language to realize the association rule mining of a restaurant company's dish data by using Apriori algorithm. Then the association rules of the dishes obtained are visualized by the R language expansion package. The frequent itemset no less than the minimum support and minimum confidence is found out and it is applied to mining the value information between dishes. The mining results show that homemade preserved pork, celery kidneys and braised pork are of strong association. The excavation results provide a basis for the recommendation of catering company and the formulation of setting meal plans, thereby increasing the corporate income.
Keywords
Association rules; Apriori algorithm; dish association analysis; R language
Cite this paper
Xiaoyang Zheng, Yue Yu, Ziming Fang, Ling Huang,
Association analysis of dishes in Catering Enterprise
, SCIREA Journal of Computer.
Volume 5, Issue 3, June 2020 | PP. 74-79.
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