Evolving interest based user groups using PSO algorithm

Any Web site may have the continuous improvement based on the getting information of the users´ needs. There is a step to achieve it by the collection of users´ search data and analysis of those data. The swarm intelligence technique of Particle Swarm Optimization(PSO) is applied for evolving similar user groups. PSO is important to identify the web users´ travels with the same interests. The data set comprises of web log files obtained by collecting the user logs during a six month period. The PSO algorithm is attempted for user categorization. In web search, the users are grouped into different categories based on their similar travels. The grouping performance of the PSO technique is compared with the techniques of DBSCAN and Kmeans.