基于机器学习PAI的网上购书推荐系统实验研究  

Experimental Research on Online Book Recommendation System Based on Machine Learning PAI

作　　者：叶小芹 王峻松 YE Xiao-qin;WANG Jun-song(Department of Mechanical and Electrical Engineering,City University of Hefei,Hefei 230000,China)

机构地区：[1]合肥城市学院机械与电气工程系,安徽合肥230000

出　　处：《辽宁工业大学学报（自然科学版）》2022年第2期106-110,共5页Journal of Liaoning University of Technology(Natural Science Edition)

基　　金：安徽省省质量工程高水平一流课程-课程类建设项目(2020kfkc172);合肥城市学院校级重点质量工程项目-教学团队(cj2020jxtd001)。

摘　　要：网络购物已成趋势,为满足商家能成功地把自己的商品推荐出去,以网络购书为例,提出了图书商品推荐系统。该系统基于机器学习平台PAI,使用协同过滤推荐算法,最终完成了图书商品推荐的任务,对图书电商的持久发展具有深远的意义。Nowadays,online shopping has become a trend.In order to meet the needs of merchants to successfully recommend their own products,the paper takes online book purchases as an example,and proposes a book product recommendation system.The system is based on the machine learning platform PAI and uses the collaborative filtering recommendation algorithm to finally complete the task of book product recommendation,which has far-reaching significance for the lasting development of book e-commerce.

关 键 词：推荐 发展 图书 电商 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]