Abstract
There was a problem that it was difficult to carry out a synthetic evaluation of mass records in database or data warehouse with traditional ways, and a feedback comprehensive evaluation method based on data mining was presented. It was completed in five steps through a feedback control system. Case study shows that the decision trees or association rules from the mining results can perform the comprehensive assessment. The puzzle that large-scale data objects is too complicate to assess at the same time is solved with this method, which improves assessment efficiency and quality greatly, reducing the workload for decision support. It is an effective complement to the traditional evaluation theory.
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References
Wei, B., Wang, S.L.: Fuzzy comprehensive evaluation of district heating system. Energy Policy (2010)
Jiawei, H., Micheline, K.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Francisco (2006)
Da, G., Martino, S.: Mining Structured Data. IEEE Computational Intelligence Magazine 147, 42–49 (2010)
Wu, X., Huacheng, Z., Huimin, Z.: Study of comprehensive evaluation method of undergraduates based on data mining. In: The 2010 IEEE International Conference on Intelligent Computing and Integrated Systems, pp. 541–543. IEEE Press, Guilin (2010)
Wu, X., Huimin, Z.: Design and Implementation of Data Warehouse of Minor Chain Supermarkets. In: The 3rd International Conference on Intelligent Computing and Intelligent Systems, pp. 828–830. IEEE Press, Xiamen (2010)
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Xie, W., Zhang, H., Meng, Z. (2011). A Feedback Comprehensive Evaluation Method with Data Mining. In: Lin, S., Huang, X. (eds) Advanced Research on Computer Education, Simulation and Modeling. CESM 2011. Communications in Computer and Information Science, vol 176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21802-6_21
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DOI: https://doi.org/10.1007/978-3-642-21802-6_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21801-9
Online ISBN: 978-3-642-21802-6
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