A Framework to Enhance Performance of E-Shopping
N. Jayakanthan1, M. Manikantan2, R. Rassika3
1N. Jayakanthan, Assistant Professor SRG, Department of Computer Applications, Kumaraguru College of Technology Coimbatore (Tamil Nadu), India.
2M. Manikantan, Assistant Professor SRG, Department of Computer Applications, Kumaraguru College of Technology Coimbatore (Tamil Nadu), India.
3R. Rassika, PG Scholar, Department of Computer Applications, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 06 September 2019 | PP: 582-584 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F11180886S19/19©BEIESP | DOI: 10.35940/ijeat.F1118.0886S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: E-shopping is a trend in present scenario. Today the shopping in internet is become a culture and habit of people. Lot of E-commerce merchants are available in market. But the online shopping system suffers a lot with various issues like performance overhead, slow response, late and error prone deliveries. Hence it is essential to enhance the performance on the online shopping system. In this paper we propose a model “Shop IT” to address the above issues. It uses greedy based “Route Mapper Algorithm” to find the shortest route between the cities and constraint based “Optimum Grouping” algorithm to group the items in the appropriate cluster. The proposed algorithm solves the performance issues.
Keywords: Online Shopping, Clustering, Shortest Path, Optimum Grouping.
Scope of the Article: Patterns and Frameworks