Personalized recommendation algorithm is core to recommendation systems, which matters the quality of recommendations of such system. The paper proposed an improved Slope one recommendation algorithm, M-Slope one. Based on real-time user interest model, the new method can calculate similarities between users and establish neighboring user groups to narrow down search scope of related items and improve the average rating differential equation for items. The algorithm proves its effectiveness for improving the precision of recommendations.
목차
Abstract 1. Introduction 2. Collaborative Filtering Recommendation Algorithm based on User Interest Model 2.1. Description of the Algorithm 2.2. Collaborative Filtering Recommendation Algorithm based on Real-time User Interest Model 3. Improved Slope One Recommendation Algorithm 3.1. Slope One Algorithm 3.2. M-Slope One Algorithm 4. Experiment Design and Discussion 4.1. Experiment Data and Development Environment 4.2. Method of Assessment 4.3. Validation of Real-time User Interest Model and the Update Model 4.4. Experimental Validation of M-Slope One Algorithm 5. Conclusion References
키워드
User Interest ModelSlope oneRecommended Algorithm
저자
Liu Lijun [ Department of Logistics Information, Hunan Vocational College of Modern Logistics,Changsha 410131,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.5