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An Improved Intellectual Analysis Precedence and Storage for Business Intelligence from Web Uses Access Data

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Computational Advancement in Communication Circuits and Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 335))

Abstract

With the growth of data mining web usage, user behaviour analysis is a useful area for business intelligence. There are several techniques to extract interesting pattern and knowledge which will be used for business intelligence from user’s access records. However, analysis of large Web log files is a convoluted task not fully addressed by existing web access techniques. In order to provide better storage and user behaviour from huge datasets the proposed intellect storage, precedence analysis (ISPA) algorithm has been introduced. The user session and history are considered as feedback for clustering. The proposed system considers the total number of hits, time spent by the user on a particular page and links. Based on these parameters, personalization has been proposed. The implementation of an effective pruning technique and FP-growth algorithm has provided better results and performance. This also considers outlier detection in order to group the links effectively. Experimental results are presented using user click through logs to validate the effectiveness of the proposed methods.

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Author information

Authors and Affiliations

  1. Department of Computer Applications, Nehru Institute of Engineering and Technology, Coimbatore, Tamilnadu, India

    S. Ganeshmoorthy

  2. Nehru Institute of Engineering and Technology, Coimbatore, Tamilnadu, India

    M. R. Bharath Kumar

Authors
  1. S. Ganeshmoorthy
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  2. M. R. Bharath Kumar
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Corresponding author

Correspondence to S. Ganeshmoorthy .

Editor information

Editors and Affiliations

  1. School of Electronics & Computer Science, University of Southampton, Southampton, United Kingdom

    Koushik Maharatna

  2. Design & Growth, Institute of Materials Research & Engg, Singapore, Singapore

    Goutam Kumar Dalapati

  3. Electronics and Telecommunication Engg, Jadavpur University, Kolkata, West Bengal, India

    P K Banerjee

  4. Electronics and Electrical Communication, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India

    Amiya Kumar Mallick

  5. Centre for Millimeter Wave Semiconductor Devices and Systems, Defence Research and Development Org., Kolkata, West Bengal, India

    Moumita Mukherjee

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Ganeshmoorthy, S., Bharath Kumar, M.R. (2015). An Improved Intellectual Analysis Precedence and Storage for Business Intelligence from Web Uses Access Data. In: Maharatna, K., Dalapati, G., Banerjee, P., Mallick, A., Mukherjee, M. (eds) Computational Advancement in Communication Circuits and Systems. Lecture Notes in Electrical Engineering, vol 335. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2274-3_28

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  • DOI: https://doi.org/10.1007/978-81-322-2274-3_28

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2273-6

  • Online ISBN: 978-81-322-2274-3

  • eBook Packages: EngineeringEngineering (R0)

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