摘要
研究电子商务平台中重复购买客户预测模型,构造出多层神经网络。原始数据编码采用词嵌入的方式,对子模块的特征向量设计出来之后设计顶层重复购买预测模型和算法。通过客户的行为日志对潜在重复购买客户进行预测具有重要意义。该预测模型适用于电子商务平台的重复购买预测,并取得了较好的效果。
This paper studies the prediction model of repeat purchase in e-commerce platform,constructs a mufti-layer neural network.The original feature data is encoded by word embedding method,and after designing the feature vectors of the sub-modules,the design to the top-level repeat purchase prediction model and algorithm is finished.It is of great practical significance to predict potential repeat purchase customers by using customer behavior log data.This prediction model is suitable for the prediction of repeated purchase of e-commerce platform,and has achieved good results.
作者
解姗姗
XIE Shan-shan(School of Information Management,Minnan Universityof Science and Technology,Shishi Fujian 362700,China)
出处
《长春工程学院学报(自然科学版)》
2020年第1期97-100,共4页
Journal of Changchun Institute of Technology:Natural Sciences Edition
基金
2018年福建省中青年教师教育科研项目基金名称(JT180690)。
关键词
重复购买
神经网络
特征向量
repeat purchase
neural network
feature vector