RETRACTED ARTICLE: Deep Learning-Assisted Heuristic Data Management in the E-Commerce Recommendation System

Abstract

Nowadays, recommendation systems are being used by an ever-increasing number of E-commerce platforms to help customers locate goods to purchase. Recommendation systems aid e-commerce sites in increasing sales and analysis at market-leading locations. Recommendation systems leverage product information, expert knowledge from customer behavior to direct customers around the often challenging task of locating products they want. Further, this paper proposed the Deep Learning-Assisted Heuristic Data Management (DLHDM) for customer purchasing data management to improve e-commerce sales. The proposed DLHDM to identify customer data correctly described, categorized, and stored for customers can quickly find what they are looking for be positive in buying decisions. Heuristic data management is useful for the development of buyer individuals or shopper profiles. This helps users to decide which product they like best and when users typically buy customer preferences. The results show the effectiveness of recommender systems and consumer recommendations for their corresponding trade-offs.