TY  - JOUR
T1  - Cluster Optimization for Improved Web Usage Mining Using WebBEE
AU - Alphy, Anna AU - Prabakaran, S. 
JO  - International Journal of Soft Computing
VL  - 10
IS  - 1
SP  - 19
EP  - 24
PY  - 2015
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2015.19.24
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2015.19.24
KW  - Chromosomes
KW  -cluster optimization
KW  -swarm intelligence
KW  -user profiles
KW  -web usage mining
AB  - Rapid development of computer technology allows as accessing huge amount online information’s. Next e-Business requirement will be personalizing or customizing the web pages according to the requirement of individuals. Personalization involves learning user’s navigational behavior. Web personalization uses web usage mining techniques to customize the web pages. The web usage mining uses data mining techniques to discover interesting usage patterns from web data. The web pages having similar usage pattern are clustered. As users increases or growth in interest of users the size of the cluster increases and it will become inevitable need to optimize clusters. This study proposes a cluster optimizing methodology based on honey bees foraging behavior and is used for eliminating the data redundancies that may occur after the clustering done by web usage mining methods. Genetic clustering is used for the process of clustering. “WebBEE approach for cluster optimization” is presented to personalize web pages for target users.
ER  -