Title :
Research of anomaly detection of laboring statistical data based on DBSCAN cluster algorithm
Author :
Li Peng-lin ; Ruan Jin-jing
Author_Institution :
Inst. of Comput. Network Applic., Zhejiang Univ. of Technol., Hangzhou, China
Abstract :
Traditional data analysis becomes harder and harder to satisfy the need of the socioeconomic development in the field of statistics. Basing on principles and method of data mining, this paper applies the DBSCAN algorithm to anomaly detection of laboring statistical data and determines the parameters according to the trait of laboring statistical data. Then detect abnormal data in statistics data by clustering and provide suggestions of the random inspection.
Keywords :
data analysis; data mining; government data processing; pattern clustering; statistical analysis; DBSCAN cluster algorithm; anomaly data detection; data analysis; data mining method; laboring statistical data; random inspection; socioeconomic development; Anomaly detection; DBSCAN cluster algorithm; Laboring statistical data;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6526181
