A Prediction Study on E-commerce Sales Based on Structure Time Series Model and Web Search Data

被引：0
|
作者：
Dai Wei [1 ]
Peng Geng [1 ]
Liu Ying [1 ]
Li Shuaipeng [1 ]
机构：
[1] Univ Chinese Acad Sci, Beijing 100090, Peoples R China
来源：
26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC) | 2014年
关键词：
search data; structure time series; sales prediction;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
With the development of e-commerce, online shopping has become a primary channel for consumers, and it is meaningful to predict the sales volume of e-commerce. This paper combines web search data and structure time series model to predict the women's clothing sales volume of Taobao. Firstly, explore the correlation of consumers' web search behavior and purchase behavior theoretically; Secondly, eliminate the trend and the seasonal factors of sales volume using structure time series model and calculate the residual series. Then construct the search index and establish the prediction model based on search data and residual of sales volume. The result shows that the mean absolute percentage error of 7-days sales volume prediction is 4.84%.
引用
收藏
页码：5346 / 5351
页数：6
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