一种基于深度学习的电子商务满意度评估方法  

An E-Commerce Satisfaction Evaluation Method Based on Deep Learning

作　　者：王红梅[1] WANG Hongmai(Nanjing College of Information Technology,Nanjing 210013,China)

机构地区：[1]南京信息职业技术学院电子商务教研室,南京210013

出　　处：《电子器件》2020年第1期196-199,共4页Chinese Journal of Electron Devices

基　　金：2016年江苏省高校哲学社会科学研究指导项目(2016SJD880037)。

摘　　要：随着电子商务的崛起,越来越多的消费者选择通过网购来获取所需的商品。消费者评论信息中包含了对商品、物流等电子商务各方面的满意程度,这就使得在线商品评论信息成为研究电子商务满意度的重要参考依据。因此充分分析商品评论中的消费者满意程度,具有巨大的商业价值和社会价值。本文从意见挖掘的角度出发,提出了一种基于深度学习的电子商务满意度评估方法,旨在为消费者进行网购决策时提供一些指导建议。With the rise of e-commerce,more and more consumers have chosen to acquire the required products through online shopping.The consumer review information includes the degree of satisfaction with various aspects of e-commerce such as commodities and logistics,which makes online product review information an important reference for research on e-commerce satisfaction.Therefore,a full analysis of consumer satisfaction in commodity reviews has enormous commercial and social value.From the perspective of opinion mining,this paper proposes an evaluation method for e-commerce satisfaction based on deep learning,which aims to provide some suggestions for consumers when making online shopping decisions.

关 键 词：电子商务满意度 意见挖掘 深度学习 

分 类 号：F713.36[经济管理—产业经济]