支持向量机的电子商务用户购买行为检测
Detection of E-commerce User Purchase Behavior Based on Support Vector Machine
周宓1
作者信息
- 1. 泉州师范学院 数学与计算机科学学院,福建 泉州 362000
- 折叠
摘要
阐述数据挖掘中的支持向量机方法,介绍客户关系管理(RFM)模型,建立基于支持向量机的电子商务用户购买行为检测模型,并用该模型进行了电子商务用户购买行为检测实验.结果表明:基于支持向量机的电子商务用户购买行为检测方法可帮助商家进行用户购买行为检测,为电子商务企业提供决策依据.
Abstract
This article elaborates on the support vector machine method in data mining,introduces the customer relationship manage-ment(RFM)model,establishes a e-commerce user purchase behavior detection model based on SVM,and conducts e-commerce user purchase behavior detection experiments using this model.The results indicate that the e-commerce user purchase behavior detection method based on SVM can help merchants detect user purchase behavior and provide decision-making basis for e-commerce enterprises.
关键词
客户关系管理/电子商务用户/用户购买行为/支持向量机/巴氏距离Key words
customer relation ship management/e-commerce users/user purchase behavior/support vector machine/bhattacharyya引用本文复制引用
基金项目
福建省中青年教师教育科研项目(科技类)(JAT210312)
出版年
2024
NETL
NSTL
万方数据