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International Conference on Web Information Systems and Mining

WISM 2011: Web Information Systems and Mining pp 109–113Cite as

The Genetic Algorithm in the Test Paper Generation

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6987))

Abstract

Genetic Algorithm has the dynamic performance and the auto adaptability. The algorithm can search the solution glibly and include the operation of coding, selection, intercross, mutation of the chromosome. The search starts from an initial cluster and reduces the probability of falling in local optima. In the test paper auto-generation, it can satisfy the requirement of the test paper generation system, improve the quality and efficiency of extracting the subjects from the test bank.

China Postdoctoral Science Foundation funded project (20100471691).

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References

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Author information

Authors and Affiliations

  1. School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, 510665, China

    Jian-Jun Hu

  2. School of Computer, South China Normal University, Guangzhou, 510631, China

    Yue-Hong Sun & Qing-Zhen Xu

Authors
  1. Jian-Jun Hu
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  2. Yue-Hong Sun
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  3. Qing-Zhen Xu
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Editor information

Editors and Affiliations

  1. Department of Computer and Inforamtion Science, University of Macau, Av. Padre Tomás Pereira, Taipa, Macau, China

    Zhiguo Gong

  2. School of Computer, Shanghai University, 200444, Shanghai, China

    Xiangfeng Luo

  3. College of Computer and Software, Taiyuan University of Technology, 030024, Taiyuan, China

    Junjie Chen

  4. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  5. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Hu, JJ., Sun, YH., Xu, QZ. (2011). The Genetic Algorithm in the Test Paper Generation. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds) Web Information Systems and Mining. WISM 2011. Lecture Notes in Computer Science, vol 6987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23971-7_16

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  • DOI: https://doi.org/10.1007/978-3-642-23971-7_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23970-0

  • Online ISBN: 978-3-642-23971-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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