A Generalization-Based Approach to Clustering of Web Usage Sessions
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Knowledge discovery from users Web-page navigation
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
Particle Swarm Optimization Based Clustering of Web Usage Data
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
In-depth behavior understanding and use: The behavior informatics approach
Information Sciences: an International Journal
An application of particle swarm optimization algorithm to clustering analysis
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on Digital Information Forensics
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Efficiency and quality of the product of data mining process is a challenging question for the researchers. Different methods have been proposed in the literature to tackle these problems. Optimization based methods are a way to address this issue. We addressed the problem of data clustering by implementing swarm intelligence based optimization technique called Particle Swarm Optimization (PSO). We scaled the approach to implement it in a hierarchical way using Hierarchical Particle Swarm (HPSO) clustering. The paper also aims to outline our novel outlier detection technique. The research will lead us to provide a benchmark for web usage mining and propose a collective intelligence based recommender system for the usage of Java API documentation.