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An Improved Apriori Algorithm

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Applied Informatics and Communication (ICAIC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 224))

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Abstract

Association rules mining occupies an important position in data mining. In order to improve the efficiency of mining of frequent itemsets, contrapose the two key problems of reducing the times of scaning the transactional database and reducing the number of candidate item sets, an improved algorithm is presented based on the classic Apriori algorithm. The theoretical analysis and test results show that the improved algorithm is better than Apriori algorithm significantly on efficiency.

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Author information

Authors and Affiliations

  1. College of Information & Electronic Engineering, Zhejiang Gongshang University, No.18, Xuezheng Str., Xiasha University Town, Hangzhou, 310018, P.R. China

    Jianlong Gu, Weiming Wang & Ming Gao

  2. National Digital Switch System Engineering and Technological R&D Center, The PLA Information Engineering University, Zhengzhou, 450002, P.R. China

    Baojin Wang & Fengyu Zhang

Authors
  1. Jianlong Gu
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  2. Baojin Wang
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  3. Fengyu Zhang
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  4. Weiming Wang
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  5. Ming Gao
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Editor information

Editors and Affiliations

  1. Shenzhen University, Nanhai Ave. 3688, 518060, Shenzhen, Guangdong, China

    Dehuai Zeng

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© 2011 Springer-Verlag Berlin Heidelberg

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Gu, J., Wang, B., Zhang, F., Wang, W., Gao, M. (2011). An Improved Apriori Algorithm. In: Zeng, D. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23214-5_18

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  • DOI: https://doi.org/10.1007/978-3-642-23214-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23213-8

  • Online ISBN: 978-3-642-23214-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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