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Simulation System of Examination Score Analysis Based on an Improved Apriori Algorithm

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Advances in Computer Science and Engineering

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 141))

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Abstract

This paper introduces an improved algorithm based on Apriori algorithm to analysis examination score. The new algorithm is implemented with vertical data layout, breadth first searching, and intersecting. It takes advantage of the efficiency of vertical data layout and intersecting, and prunes candidate frequent item sets like Apriori. Finally, the new algorithm is applied in simulation system of examination score analysis. The result shows that the relations will be affected by the students’ grades, and it can be applied in guiding students’ study and teachers’ teaching practice.

This work was supported by the Natural Science Foundation of Huai’an Technology under Grant HAG2010068.

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References

  1. Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of item s in large databases. In: Proc of ACM SIGMOD Conference on Management of Data, pp. 207–216. ACM, New York (1993)

    Google Scholar 

  2. Agrawal, R., Srikant, R.: Fast algorithm form ining association rules in large databases. In: Proceedings of the 20 th International Conference on Very Large Data Bases, pp. 487–499. Morgan Kaufmann Publishers Inc., San Francisco (1994)

    Google Scholar 

  3. Zaki, M.J., Parthasarathy, S., Ogihara, M., Li, W.: New algorithms for fast discovery of association rules. In: Proc. of the 3 rd Intpl Conf. on KDD and DataMining (KDD 1997), NewportBeach, California (August 1997)

    Google Scholar 

  4. Han, J.W., Micheline, K.: Data Mining Concepts and Techniques. Machinery Industry Press, Beijing (2002); Fan Ming, Meng Xiaofeng,Translated

    Google Scholar 

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Correspondence to Li Xiang .

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Xiang, L. (2012). Simulation System of Examination Score Analysis Based on an Improved Apriori Algorithm. In: Zeng, D. (eds) Advances in Computer Science and Engineering. Advances in Intelligent and Soft Computing, vol 141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27948-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-27948-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27947-8

  • Online ISBN: 978-3-642-27948-5

  • eBook Packages: EngineeringEngineering (R0)

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