摘要
随着互联网的发展,个性化推荐系统的需求逐渐增加。传统的推荐算法面临冷启动问题,而基于聚类分析和人工智能的个性化推荐算法可以很好地解决此问题。本文介绍了该算法的基本思想和实现过程,并对其进行了评估和分析。实验结果表明,与传统算法相比,该算法在准确性、稳定性和效率方面都更优秀。
With the development of the Internet,the demand for personalized recommendation systems has gradually increased.Traditional recommendation algorithms face the problem of cold start,while personalized recommendation algorithms based on cluster analysis and artificial intelligence can solve this problem well.This paper introduces the basic idea and implementation process of the algorithm,and evaluates and analyzes it.The experimental results show that the algorithm is superior to traditional algorithms in terms of accuracy,stability and efficiency.
作者
盛少军
SHENG Shaojun(Amazon(China)Holding Co.,Ltd.,Beijing 100025,China)
出处
《自动化应用》
2023年第17期43-45,共3页
Automation Application
关键词
个性化推荐
聚类分析
人工智能
准确性
personalized recommendation
cluster analysis
artificial intelligence
accuracy
