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Application of Particle Swarm Optimization and User Clustering in Web Search

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Computational Intelligence in Data Mining - Volume 2

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 32))

Abstract

User clustering is the most significant process in web usage mining. This approach tries to generate the clusters of users with the similar travels in the web search. Preprocessing is needed to extract the relevant data which is used for user clustering. Now a day Particle Swarm Optimization (PSO) approach is used in web search applications. This paper applies a Particle Swarm Optimization algorithm to web user grouping in association with the Open Directory Project (ODP) dataset. The experimental result shows that the effectiveness of Particle Swarm Optimization to be a suitable approach for web user clustering as compared to the K-means and DB-Scan clustering methods.

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Authors and Affiliations

  1. Department of Information Science and Technology, CEG Campus, Anna University, Chennai, 600025, Tamil Nadu, India

    Sumathi Ganesan & Sendhilkumar Selvaraju

Authors
  1. Sumathi Ganesan
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  2. Sendhilkumar Selvaraju
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Corresponding author

Correspondence to Sumathi Ganesan .

Editor information

Editors and Affiliations

  1. University of Canberra, Canberra, Australia and University of South Australia, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  2. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Ganesan, S., Selvaraju, S. (2015). Application of Particle Swarm Optimization and User Clustering in Web Search. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 2. Smart Innovation, Systems and Technologies, vol 32. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2208-8_39

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  • DOI: https://doi.org/10.1007/978-81-322-2208-8_39

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2207-1

  • Online ISBN: 978-81-322-2208-8

  • eBook Packages: EngineeringEngineering (R0)

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