Title :
Clustering heterogeneous web usage data using Hierarchical Particle Swarm Optimization
Author :
Alam, Shahinur ; Dobbie, Gillian ; Koh, Yun Sing ; Riddle, Patricia
Author_Institution :
Dept. of Comput. Sci., Univ. of Auckland, Auckland, New Zealand
Abstract :
Data clustering aims to group data based on similarities between the data elements. Recently, due to the increasing complexity and amount of heterogenous data, modeling of such data for clustering has become a serious challenge. In this paper we tackle the problem of modeling heterogeneous web usage data for clustering. The main contribution is a new similarity measure which we propose to cluster heterogeneous web usage data. We then use this similarity measure in our Particle Swarm Optimization (PSO) based clustering algorithm, Hierarchical Particle Swarm Optimization based clustering (HPSO-clustering). HPSO-clustering combines the qualities of hierarchical and partitional clustering to cluster data in a hierarchical agglomerative manner. We present the clustering results and explain the effects of the new similarity measure on inter-cluster and intra-cluster distances. These measures verify the applicability of the proposed similarity measure on web usage data.
Keywords :
Internet; data mining; particle swarm optimisation; pattern clustering; HPSO-clustering; data mining; data modeling; heterogeneous Web usage data clustering; hierarchical agglomerative manner; hierarchical particle swarm optimization based clustering; partitional clustering; similarity measure; Atmospheric measurements; Data mining; Equations; Java; Mathematical model; Particle measurements; Particle swarm optimization; Data clustering; Data mining; Particle Swarm Optimization; evolutionary computation;
Conference_Titel :
Swarm Intelligence (SIS), 2013 IEEE Symposium on
Conference_Location :
Singapore
DOI :
10.1109/SIS.2013.6615172