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Intelligent Computing, Networking, and Informatics pp 1089–1097Cite as

Classification Technique for Improving User Access on Web Log Data

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 243))

Abstract

In the present era, Internet is playing a significant role in our everyday life; therefore, it is very thorny to survive without it. Web log file that keeps track of the users’ access on net, if mined, can provide us precious information about the surfers. Similarly, the rapid growth of data mining applications has shown the necessity for machine learning algorithms to be applied to large-scale data. In this paper, we are using the naïve Bayesian (NB) classification technique using Weka for identifying the frequent access pattern. The main objective of this paper is to categorize browsing behavior of the user based on their position. This paper performs experiment and classifies the user access behavior from the large databases, which could result in increasing the efficiency and effectiveness of the system by reducing the browsing time of the user or results in fast retrieval of information from the system.

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Author information

Authors and Affiliations

  1. Computer Science and Engineering Department, Graphic Era University, Dehradun, India

    Bina Kotiyal & R. H. Goudar

  2. Information Technology Department, Era University, Dehradun, India

    Ankit Kumar & Bhaskar Pant

Authors
  1. Bina Kotiyal
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  2. Ankit Kumar
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  3. Bhaskar Pant
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  4. R. H. Goudar
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Corresponding author

Correspondence to Bina Kotiyal .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, Orissa, India

    Durga Prasad Mohapatra

  2. Computer Science and Engineering, SOA University, Bhubaneswar, India

    Srikanta Patnaik

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© 2014 Springer India

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Kotiyal, B., Kumar, A., Pant, B., Goudar, R.H. (2014). Classification Technique for Improving User Access on Web Log Data. In: Mohapatra, D.P., Patnaik, S. (eds) Intelligent Computing, Networking, and Informatics. Advances in Intelligent Systems and Computing, vol 243. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1665-0_111

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  • DOI: https://doi.org/10.1007/978-81-322-1665-0_111

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1664-3

  • Online ISBN: 978-81-322-1665-0

  • eBook Packages: EngineeringEngineering (R0)

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