| Issue |
MATEC Web Conf.
Volume 355, 2022
2021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
|
|
|---|---|---|
| Article Number | 02033 | |
| Number of page(s) | 5 | |
| Section | Mathematical Science and Application | |
| DOI | https://doi.org/10.1051/matecconf/202235502033 | |
| Published online | 12 January 2022 | |
Association analysis in food sampling inspection data
School of E-Business and Logistics, Beijing Technology and Business University, Beijing, China
* Corresponding author: mschenxin@163.com
At present, China exists a problem that the cost of food sampling inspection is too high. This paper attempts to reduce the number of sampling inspection items in the same food category, reduce the cost of food sampling inspection, and improve the work efficiency through the association analysis of national sampling inspection data. And this paper applies Apriori algorithm to analyse the association rules, which is based on the unqualified pastry sampling inspection data in the 2019 national food sampling inspection database. Finally, we obtain 10 strong association rules through experiments. The results show that this association analysis can reduce the workload of food sampling inspection effectively.
Key words: keywords: / Apriori algorithm / Food sampling inspection data / Data mining
© The Authors, published by EDP Sciences, 2022
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