摘要
随着电商交易量和用户数的不断增加,一方面在电商营销过程中商家调价的频率和幅度都有所增加;另一方面面对众多选择消费者难以对自己所需的商品有准确的价格估计,也无从判断现在是否处于价格高地。笔者用网络爬虫程序获取了知名大型电子商务平台以电脑为例的多个时刻的商品数据,提取有效信息字段并进行量化,最终通过多元线性回归建立了商品价格模型,并对模型的进一步应用进行了展望。
With the continuous increase in the volume of e-commerce transactions and the number of users, on the one hand, the frequency and range of price fluctuation have increased. On the other hand, facing so many choices, consumers are difficult to estimate the price of the goods they need and they don’t know whether it is at a high price. In this paper, we use the web crawler program to obtain the commodity data of a large-scale e-commerce platform with computer as an example, extract the effective information and quantify them. Finally, the price model is established by multiple linear regression. At last, this paper prospects for further application of the model.
作者
尤天琪
冯思毓
周陈雯淑
潘润超
You Tianqi;Feng Siyu;Zhou-Chen Wenshu;Pan Runchao(Nanjing Normal University,Nanjing Jiangsu 210023,China)
出处
《信息与电脑》
2019年第17期138-140,143,共4页
Information & Computer
关键词
电商交易数据
网络爬虫
数据处理
多元线性回归
价格模型
E-commerce transaction data
web crawler
data processing
multiple linear regression
price model
