DocumentCode :
3384535
Title :
Financial revenue analysis based on association rules mining
Author :
Min, Zhi ; Zhang, Rui
Author_Institution :
Inf. Center, Zhejiang Provincial Finance Bur., Hangzhou, China
Volume :
1
fYear :
2009
fDate :
28-29 Nov. 2009
Firstpage :
220
Lastpage :
223
Abstract :
In financial system, the general use of financial data has also been unable to meet the inherent need of the deepening of financial information and management modernization. The financial informationization is faced with needs of the growing use of financial data analysis. Under this background, this paper analyzes the financial income of certain city in a certain period. Association rules are mined in Weka by using apriori algorithm to those data, which have be collected, preprocessed and converted. By finding the rules and knowledge, it can provide a scientific basis for decision-making and gain valuable information for comprehensive analysis and evaluate the financial balance of payments situation in certain region.
Keywords :
data mining; decision making; financial management; Weka; apriori algorithm; association rules mining; decision making; financial informationization; financial revenue analysis; Application software; Association rules; Cities and towns; Data analysis; Data mining; Delta modulation; Economic forecasting; Finance; Financial management; Information analysis; association rules; data mining; financial revenue;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4606-3
Type :
conf
DOI :
10.1109/PACIIA.2009.5406454
Filename :
5406454
Link To Document :
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