Data Mining Research on Time Series of E-commerce Transaction

Xiao Qiang; He Rui-Chun; Liao Hui

Data Mining Research on Time Series of E-commerce Transaction

원문정보

Xiao Qiang, He Rui-Chun, Liao Hui

보안공학연구지원센터(IJUNESST) International Journal of u- and e- Service, Science and Technology Vol.7 No.1 2014.02 pp.9-18

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초록

영어

In E-commerce, data mining can help the online customers accurately grasp the sellers’ product sales, to improve the online product purchase rate. In this paper, the mining algorithm of E-commerce transaction based on time series is proposed, which analyzes the relationship between the density of E-commerce transaction recorders and product sales records in E-commerce sites by use of the method of Guass density function and sliding-window. To examine the approach by MATLAB, illustration is provided to demonstrate the effectiveness of the algorithm

Abstract
1. Introduction
2. Related Works
3. The Model of the Time Series of E-commerce
  3.1. Generate Time Series
  3.2. Calculating and Processing of Time Series
  3.3. Result Analysis and Graph Display
4. Our Approach
  4.1. Calculating the Density of Time Series
  4.2. Analyzing and Calculating by use of Sliding Window
  4.3. Calculating and Analysis of Result
5. Experiment and Result
6. Conclusion and Future Work
Acknowledgment
References

키워드

저자정보

Xiao Qiang School of Traffic and Transportation, Lanzhou Jiao tong University, Lanzhou, China, School of Economics and management, Lanzhou Jiao tong University, Lanzhou, China
He Rui-Chun School of Traffic and Transportation, Lanzhou Jiao tong University, Lanzhou, China
Liao Hui School of Economics and management, Lanzhou Jiao tong University, Lanzhou, China

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