E-commerce Product Recommendation System Using Enhanced Product Visibility - Nitin Upadhyay, Dr. Deepika Pathak (Mathematical Statistician and Engineering Applications, 2021)
E-commerce is becoming much more popular in recent years. A significant amount of e-commerce consumers increased as well as new product vendors also increased in order to get benefit from this open market. But the new product vendors are suffering from low product sales. Therefore, in order to enhance the product visibility of the new vendors needs some improvements on the existing recommendation system. The current recommendation algorithms consider the products based on ratings and reviews, their existing sales, and brand size. Therefore, the new vendors feel the biased nature of any e-commerce platform. The next option is to enhance the product visibility using advertisements which may be much more expensive for new vendors. Therefore, this paper presents a new e-commerce product recommendation model, which provides a win-win situation for all the parties’ consumers, vendors, and e-commerce platform administrators. The proposed model also suggests key points that can be considered during the design of an e-commerce business. Additionally, a weighted recommendation system is proposed and evaluated for recommending a set of products to existing customers. The proposed model utilizes a feedback model for refining and recommending products to consumers.