Product Recommendation System for E-Commerce Website |
Author(s): |
Taha Basrwala , Medi-Caps Institute of Science and Technology; Shimpy Goyal, Medi-Caps Institute of Science and Technology; Aziz Saifee, Medi-Caps Institute of Science and Technology; Swapnil Gupta, Medi-Caps Institute of Science and Technology |
Keywords: |
Recommender Systems, E-Commerce, Behaviour Analysis, Interface, Customer Loyalty, Cross-Sell, Up-Sell, Mass Customization |
Abstract |
Recommender systems are Nowadays heavily used by some e-commerce websites. It has become a serious business tool. This led to a big change in the world of e-commerce. Many of the most important commerce websites are already using recommender systems to help their customers find products to shop for. A recommender system learns from a customer and recommends products that he/she's visiting find Most worthy from among the available products. during this paper, we present a symbol of how recommender systems help E-commerce sites increase sales, and analyse five sites that use recommender systems including several sites that use over one recommender system. supported the examples, we create a taxonomy of recommender systems, including the interfaces they present to customers, analysing the behaviour of consumers over different products, the technologies used to create the recommendations, and also the inputs they need from customers. We conclude with ideas for fresh applications of recommender systems to E-commerce. |
Other Details |
Paper ID: IJSRDV9I120157 Published in: Volume : 9, Issue : 12 Publication Date: 01/03/2022 Page(s): 180-184 |
Article Preview |
|
|