High Impact Factor : 4.396 icon | Submit Manuscript Online icon | UGC Approved icon

User Adaptive E-Commerce Website

Author(s):

Akshay Palekar , Atharva College of Engineering, Mumbai University,Mumbai, India; Anmol Sahota, Atharva College of Engineering, Mumbai University,Mumbai, India; Bhushan Parmar, Atharva College of Engineering, Mumbai University,Mumbai, India; Mihir Desai, Atharva College of Engineering, Mumbai University,Mumbai, India; Manisha Giri, Atharva College of Engineering, Mumbai University,Mumbai, India

Keywords:

Apriori Algorithm, Association Rules, Support Vector Machine

Abstract

E-commerce websites today have become highly sensitive towards the end user’s needs. The data that is available on these websites is very systematically categorized so as to give the user a seamless experience. The technique that we are proposing takes into account the behaviour of the user on the website. Whenever a specific user logs on to his or her account, their surfing history is logged. Apriori Algorithm is used to find the Association Rules which determine patterns in the customer usages. Support Vector Machine will help determine the preferences of the user. Whenever the client makes a purchase on the website the transaction is recorded and in time a user profile is generated as to what a specific user finds interesting on the website. So on the next visits on the webpage the user is given a more personalized experience

Other Details

Paper ID: NCTAAP099
Published in: Conference 4 : NCTAA 2016
Publication Date: 29/01/2016
Page(s): 419-421

Article Preview




Download Article