Title :
The GSP algorithm in dynamic cost prediction of enterprise
Author :
Chengguan Xiang ; Shihuan Xiong
Author_Institution :
Guizhou Normal Coll., Guiyang, China
Abstract :
By making use of the previous result of sequential pattern mining, a projection database will be build to help decrease the scanning times of the whole database and the creation of the candidate sequence, which can make up for the weakness of the GSP. In this way, the mining efficiency is enhanced; the demand of the computing speed of the massive data is satisfied. So it is convenient to search for the right cost information from the massive data and then to proceed with cost analysis and cost prediction. The application of the improved time sequential pattern to the cost prediction in the enterprises demonstrates that this kind of computing system can enhance the accuracy and promptness of cost prediction effectively.
Keywords :
costing; data mining; financial data processing; pattern clustering; prediction theory; GSP algorithm; computing system; cost analysis; cost information; data mining efficiency; dynamic cost prediction; generalized sequential pattern mining; projection database; time sequential pattern; Algorithm design and analysis; Data mining; Databases; Heuristic algorithms; Prediction algorithms; Productivity; Cost Analysis; Cost Prediction; GSP Algorithm; Massive Data; Time Sequential Pattern Mining component;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022400
