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Frontiers in Signal Processing
FSP > Volume 4, Number 1, January 2020

Research on Audit Application Based on Apriori Algorithm

Download PDF  (355.5 KB)PP. 10-15,  Pub. Date:October 10, 2019
DOI: 10.22606/fsp.2020.41002

Author(s)
Honglei Chu, Daji Ergu
Affiliation(s)
Key Laboratory of Electronic and Information Engineering, Southwest Minzu University, Chengdu, China
Key Laboratory of Electronic and Information Engineering, Southwest Minzu University, Chengdu, China
Abstract
The data analysis is very important in the audit field since there are plenty of audit big data, which cannot be identify easily. This paper applies one of the big data techniques to the audit work and solves the problem that is hard to be found in the hidden information data. Specifically, the Apriori algorithm is used to mine and analyze the audited personnel's learning test data in the audit data to form the association rules, and the results can provide guidance for the next audited personnel training and testing. Firstly, the test data is preprocessed and the data is discretized; then the Apriori algorithm is used in the Python language environment, and the processed data is used to mine the association rules, and the impact of the audited personnel is found in the formed association rules. The rules of the results are analyzed.
Keywords
Audit work, data mining, Apriori algorithm, test data.
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