Title :
Application of Hierarchical Clustering in Tax Inspection Case-Selecting
Author :
Liu, Xiaoqing ; Pan, Ding ; Chen, Shihong
Author_Institution :
Jinan Univ., Guangzhou, China
Abstract :
Nowadays, some enterprises have multiplicative ways of going about tax evasion, which becomes one puzzle in tax inspection. Tax inspectors to carry out rapid and accurate work have become extremely important. The traditional inspection case-selecting is mainly based on reported information. This method to judge the delineation of the characteristics of those unscrupulous taxpayers largely depends on the past experience and some intuition of the professional inspectors. This paper uses the hierarchical clustering in the tax inspection case-selecting. First, this paper describes the theory of clustering. Second, it analyses the index data of 30 enterprises using the hierarchical clustering and gets the analyzing result. Finally, the result is compared with the known taxation case. Then we get the conclusion that the hierarchical clustering method can assist the case-selecting and can improve the efficiency and effect of the tax inspection.
Keywords :
data mining; pattern clustering; taxation; data mining techniques; hierarchical clustering method; tax evasion; tax inspection case-selecting; Algorithm design and analysis; Clustering algorithms; Clustering methods; Data mining; Finance; Indexes; Inspection;
Conference_Titel :
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5391-7
Electronic_ISBN :
978-1-4244-5392-4
DOI :
10.1109/CISE.2010.5676711