基于机器学习算法的在线推荐系统设计与性能优化研究  

Research on Design and Performance Optimization of Online Recommendation System Based on Machine Learning Algorithm

作　　者：魏芬[1] WEI Fen(Wuhan City Polytechnic,Wuhan Hubei 430000,China)

机构地区：[1]武汉城市职业学院,湖北武汉430000

出　　处：《信息与电脑》2024年第3期89-91,共3页Information & Computer

摘　　要：传统运营方式已经难以应对日益复杂的业务场景。特别是电商领域,采用个性化推荐系统对于改善用户体验、促进商品销售、提高广告点击率具有重要意义。文章以电商场景为例,设计了基于机器学习算法的在线推荐系统,并对该系统进行了性能优化。Traditional operational methods are no longer able to cope with increasingly complex business scenarios.Especially in the e-commerce field,adopting personalized recommendation systems is of great significance for improving user experience,promoting product sales,and increasing ad click through rates.In this paper,an online recommendation system based on machine learning algorithm is designed,and the performance of the system is optimized.

关 键 词：机器学习算法 在线推荐系统 性能优化 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]