International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 182 - Number 38 |
Year of Publication: 2019 |
Authors: Pankaj Pandey, Sneha Soni |
10.5120/ijca2019918405 |
Pankaj Pandey, Sneha Soni . Enhance Clustering Approach using PSO-A* for E-Commerce. International Journal of Computer Applications. 182, 38 ( Jan 2019), 57-60. DOI=10.5120/ijca2019918405
In the current trends most of the people uses online searching and purchasing the items. So web data size is drastically increases and after some time not possible to put all data in memory. So there is a need to manage data access speed and also increase the speed of searching. In the existing system most of clustering algorithm uses only basic criteria for machine learning and data mining algorithms. Initially it is not able to select the good center point so it will do to increase the number of iteration. Second problem is to access of full database and third problem is needed to increase searching speed. The proposed approach uses PSO-A* algorithm for clustering and searching that is used for select the good center point initial for clustering. After that only clustered data is access not full database that make partial database access to manage memory management and speed. Finally third approach is uses for increase searching speed. Now the proposed approach is to perform well and improve the e-commerce website performance.