Research on Intelligent Recommendation Model of E-Commerce Commodity Based on Feature Selection and Deep Belief Network

Abstract

Due to the complexity and uncertainty of customer demand behavior, it was often difficult to obtain satisfactory recommendation results by using the existing online commodity recommendation systems. Therefore, a network commodity intelligent recommendation model based on feature selection and deep belief network was proposed. Based on the basic structure and function of the existing recommendation systems, this paper expounded the interaction process between customers, e-commerce platforms, enterprises, and the recommendation system. By analyzing the internal relationship between customer demand and commodity recommendation, the relationship model between customer demand and commodity recommendation was established. After analyzing the characteristics of customers’ demand for goods, a data mining method was used to classify the characteristics of customers’ demand behavior, and a feature selection method based on deep belief network (DBN) was proposed to obtain the main information conducive to commodity recommendation. Finally, an e-commerce commodity recommendation algorithm based on feature selection and deep belief network was proposed. The experimental results showed that the network commodity recommendation model proposed in this paper can not only provide customers with satisfactory recommendation results but also has better performance than other traditional recommendation models. The recommendation model proposed in this paper can support different e-commerce website recommendation systems.

Intelligent Analysis of E-commerce Reviews based on Complex-Valued Spatio-temporal Graph Convolutional Neural Network Optimized Tyrannosaurus Optimization Algorithm

“…In 2022, Li, Y., et.al, [24] have presented Research on Intelligent Recommendation Model of E-Commerce Commodity Depend on Feature Selection with Deep Belief Network. Here, described the way in which consumers, businesses, e-commerce sites, and systems for recommendation the correlation concept between consumer demand and product recommendation was built through a study of the internal connection between both of them.…”

Retracted: Research on Intelligent Recommendation Model of E-Commerce Commodity Based on Feature Selection and Deep Belief Network

“…Model of E-Commerce Commodity Based on Feature Selection and Deep Belief Network" [1] due to concerns that the peer review process has been compromised. Following an investigation conducted by the Hindawi Research Integrity team [2], signifcant concerns were identifed with the peer reviewers assigned to this article; the investigation has concluded that the peer review process was compromised.…”