Volume 11 Number 6 (Jun. 2016)
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JSW 2016 Vol.11(6): 569-576 ISSN: 1796-217X
doi: 10.17706/jsw.11.6.569-576

Applying BSC-Based Resource Allocation Strategy to IDSS Intelligent Prediction

Yun Zhang1*, Yang Chen2
1School of Computer Science and Technology, Xi’an University of Science & Technology, Xi’an 710054, Shaanxi, P.R.China.
2Thought Works Software Technologies (Xi'an) Ltd, Room 06, 6th floor, Building E Huanpu Science and Technology Industrial Park No.211 8th Tiangu Road, Hi-tech Development District Xi'an, 710077, Shanxi P.R.China.

Abstract—In this paper, a new data mining model is designed and constructed, the model is based on Balanced Score Card(BSC) and used for intelligent decision support system of data mining and prediction. On the one hand, based on data mining framework, the new data mining model come up with three different resource allocation mechanisms, emphasizing the understanding of the business process, focusing on data accuracy and covering the quality of data mining modeling. The BSC resource allocation mode and algorithm are designed with new insight perspective.On the other hand, the typical established case shows how the mining of resource allocation to improve the accuracy of intelligent prediction. Data mining based on BSC not only to provide an integration platform to support different mining components, but also be able to combine limited resources into reasonable mining process via using the resource evaluation analysis and resource allocation with purpose of improving the accuracy of the prediction and intelligent.

Index Terms—Intelligent decision support system, data mining, balanced scorecard, prediction, resource allocation.


Cite: Yun Zhang, Yang Chen, "Applying BSC-Based Resource Allocation Strategy to IDSS Intelligent Prediction," Journal of Software vol. 11, no. 6, pp. 569-576, 2016.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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