顾客感知价值视角下电商平台个性化推荐系统优化研究
Research on the Optimization of Personalized Recommendation System of E-Commerce Platform from the Perspective of Customer Perceived Value

随着新一轮信息科技的迅猛发展，电商平台的个性化推荐系统越来越多被企业和商家广泛运用。电商平台个性化推荐系统优化与提升是众多企业和商家关注的重要问题。本文立足发展新型消费，从顾客感知价值的视角，分析了电商平台个性化推荐系统存在系统用户界面老旧、系统基础功能繁琐和营销手段拘泥于传统推荐形式等问题，提出自主优化用户界面、减少用户使用系统的麻烦和利用新兴技术营销对电商平台个性化推荐系统进行功能优化及关键技术，进而分析个性化推荐系统的信息安全风险，并提出了个性化推荐的风险防范，以更好地提升消费者的价值体验，促进电商平台的企业和商家提升经营绩效。
With the rapid development of new information technology, personalized recommendation systems on e-commerce platforms are being more and more widely used by enterprises and businesses. The optimization and improvement of personalized recommendation systems on e-commerce platforms is a significant issue that many enterprises and businesses are concerned about. Based on the development of new forms of consumption and from the perspective of customer perceived value, this paper analyzes the problems existing in the personalized recommendation system on e-commerce platforms, which include the old user interface, tedious basic functions, and sticking to traditional recommendation patterns in marketing. This paper puts forward ideas of independent optimization of the user interface, reducing hassles for users using the system, and optimizing functions of a personalized recommendation system on an e-commerce platform by using emerging technologies for marketing, and key technologies. It further analyzes information security risks in the personalized recommendation system and proposes risk prevention in the terms of personalized recommendations to better enhance the value of customers’ experiences and promote enterprises and businesses with e-commerce platforms to improve their business performances.