Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

Abstract

e-commerce mode shows great modern commercial value. In particular, online shopping has become a fashion and trend for people because of its convenience and rapidness. How to find the information users that need accurately and quickly in the increasing network information and recommend products is a big problem. Although precision marketing was mainly used in e-commerce activities in the past, due to factors such as the technical basis and data analysis ability at that time, there was not enough technical ability and theoretical basis to deeply mine and make use of the existing data. The collaborative filtering algorithm is one of the most widely used and successful recommendation techniques, but it has obvious defects. In this paper, the nearest neighbor collaborative filtering recommendation algorithm based on statistical eigenvalue classification is proposed in the collaborative filtering algorithm. By calculating the similarity between items, the user’s rating of unrated items is preliminarily predicted, the nearest neighbor of items is formed, and the classified cluster of items is formed. The matrix is filled by the similarity between related items. The cold treatment problem is solved under the optimization of the ant colony algorithm. In the experiment of the model, the optimization rate for the cold start problem is 87.3%.

Functional Framework for Multivariant E-Commerce User Interfaces

“…Previous efforts were often linked to the service-oriented architecture (SOA) paradigm [14]. Today, various approaches are commonly used for personalization in adaptive web shop interfaces, including AI-based methods such as collaborative filtering (CF) [15], CF based on deep learning [16], and its modification that uses the relationships between items rather than users (item-based CF-IBCF) as the basis for inference [17], case-based reasoning (CBR) [18], the RFMT (recency, frequency, monetary, time) model [19], data mining [20], and clustering [21]. UI personalization is applicable across diverse IT systems, whether within organizations (e.g., enterprise resource planning-ERP [22]), supporting interorganizational collaboration (e.g., workflow [23]), or dedicated to customers (e.g., e-commerce [24]).…”

Retracted: Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”