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
목차
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
data miningE-commercetime seriesdensity
저자
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 ]
보안공학연구지원센터(IJUNESST) [Science & Engineering Research Support Center, Republic of Korea(IJUNESST)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of u- and e- Service, Science and Technology
간기
격월간
pISSN
2005-4246
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of u- and e- Service, Science and Technology Vol.7 No.1