The analysis of the existing recommendation system and the main task in the electronic commerce application and the existing problems of the basis, according to the new user "cold start" problem, to adopt a user in a number of different categories of electronic commerce website access multi-B2C behavior information recommendation. This paper presents a crossing ranking recommendation algorithm. Its accuracy can be far more than the random recommendation, at the same time keeping and diversity were recommended. All these ensure the algorithm has a good user experience. Experiments show that the algorithm is accurate and the algorithm is further enhanced.
목차
Abstract 1. Introduction 2. Data Analysis of Multi-B2C Behavior 3. Crossing Ranking Recommendation Algorithm of Multi-B2C Behavior 3.1. The Recommendation Algorithm Based on Two Part Graph Resource Allocation 3.2. Recommendation List 4. Experimental Analysis and Results 4.1. Dataset Partition 4.2. Correlation Algorithm 4.3. The Experimental Results of One-to-One Crossing Ranking Recommended 4.4. The Experimental Results of Many-to-One Crossing Ranking Recommended 5. Conclusion References
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.4