Title :
Research of tax inspection cases-choice based on association rules in data mining
Author :
Zhu, Qing-xiang ; Guo, Li-juan ; Liu, Jing ; Xu, Nan ; Li, Wei-xu
Author_Institution :
Sch. of Econ. & Manage., Yanshan Univ., Qinhuangdao, China
Abstract :
Association rule of data mining mainly refers to digging out an interesting correlation, opening out the unknown inter-dependence in a great deal of the data. This paper firstly set up inspection indexes for enterprise income tax, and then applies the apriori algorithm of association rules of data mining into tax inspection cases-choice. This method can accurately find the dishonest enterprise in order to improve the efficiency and effectiveness of inspection.
Keywords :
data mining; taxation; association rules; data mining; dishonest enterprise; enterprise income tax; inspection indexes; tax inspection cases-choice; Association rules; Conference management; Cybernetics; Data analysis; Data mining; Databases; Decision making; Finance; Inspection; Machine learning; Apriori algorithm; Data mining; Indicator system; Tax inspection cases-choice;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212107
