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CPPG: Efficient Mining of Coverage Patterns Using Projected Pattern Growth Technique

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Trends and Applications in Knowledge Discovery and Data Mining (PAKDD 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7867))

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Abstract

The knowledge of coverage patterns extracted from the transactional data sets is useful in efficient placement of banner advertisements. The existing algorithm to extract coverage patterns is an apriori-like approach. In this paper, we propose an improved coverage pattern mining method by exploiting the notion of “non-overlap pattern projection”. The proposed approach improves the performance by efficiently pruning the search space and extracting the complete set of coverage patterns. The performance results show that the proposed approach significantly improves the performance over the existing approach.

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Author information

Authors and Affiliations

  1. International Institute of Information Technology, Hyderabad, India

    P. Gowtham Srinivas, P. Krishna Reddy & A. V. Trinath

Authors
  1. P. Gowtham Srinivas
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  2. P. Krishna Reddy
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  3. A. V. Trinath
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Editor information

Editors and Affiliations

  1. School of Information Technology and Mathematical Sciences, University of South Australia, 1 Mawson Lakes Boulevard, 5095, Adelaide, SA, Australia

    Jiuyong Li

  2. Advanced Analytics Institute, University of Technology, 2-12 Blackfriars Street, Chippendale, Blackfriars Campus, 2008, Sydney, NSW, Australia

    Longbing Cao  & Can Wang  & 

  3. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576, Singapore, Singapore

    Kay Chen Tan

  4. School of Automation, Guangdong University of Technology, No. 100 Waihuan Xi Road, Panyu District, 510006, Guangzhou, China

    Bo Liu

  5. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  6. Department of Computer Science and Information Engineering, National Cheng Kung University, No.1, University Road, 701, Tainan, Taiwan

    Vincent S. Tseng

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© 2013 Springer-Verlag Berlin Heidelberg

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Srinivas, P.G., Reddy, P.K., Trinath, A.V. (2013). CPPG: Efficient Mining of Coverage Patterns Using Projected Pattern Growth Technique. In: Li, J., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science(), vol 7867. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40319-4_28

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  • DOI: https://doi.org/10.1007/978-3-642-40319-4_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40318-7

  • Online ISBN: 978-3-642-40319-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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