Application of Particle Swarm Optimization and User Clustering in Web Search

  • Sumathi Ganesan
  • Sendhilkumar Selvaraju
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 32)


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.


Web search User clustering Swarm intelligence Particle swarm optimization ODP taxonomy 


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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Information Science and Technology, CEG CampusAnna UniversityChennaiIndia

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