Author : Parmjeet Kaur, Usvir Kaur and Dheerendra Singh

Web search portals contains large amounts of web search data which includes keywords, links and other information. Web data association rules algorithm/s is the technique to deal with the web search data to produce the best results by analyzing the information in various combinations. In this paper, a novel web data association rule mining based hybrid algorithm called HPSO-TS-ARM has been proposed. This algorithms is based three well known high-level procedures: Particle Swarm Optimization, Tabu Search and Apriori Algorithm for Association Rule Mining. Where PSO will fetch the web search data in its optimized form, which is further computed by Tabu Search to prepare balance data arrangement followed by Association rule mining on processed web search data. The proposed algorithms have outperformed HBSO-TS and BSO-ARM on the basis of elapsed time and fitness function.

Keywords: Association Rule Mining, Particle Swarm Optimization, Tabu Search, Apriori.

Article published in International Journal of Current Engineering and Technology, Vol.4, No.5 (Oct-2014)