원문정보
보안공학연구지원센터(IJUNESST)
International Journal of u- and e- Service, Science and Technology
Vol.7 No.5
2014.10
pp.359-368
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보