Earticle

초록

영어

Considering the probability matrix decomposition model, direct trust and indirect trust, trust propagation, as well as similarity between users and other factors, this paper proposes a new recommendation algorithm which fully taps the trust mechanism, and takes into account the similarity between users. Firstly, a new trust matrix is obtained based on the trust value of social network. Then all the trust relationships are integrated into the recommendation algorithm through the RSTE model. Finally, the prediction score is produced and the recommended list is given. Experimental results on public data sets show that this recommendation algorithm has obvious feasibility and superiority.

목차

Abstract
 1．Introduction
 2. Basic Thought
 3. IAValue Calculation and Recommendation Procedure
 4. Probabilistic Graph Model
 5. Algorithm Steps
 6. Experiment and Analysis
  6.1. Data Sources
  6.2. Evaluation Index
  6.3. Contrast Algorithm
  6.4. Experimental Result
 7. Conclusion
 References

키워드

저자

• Gao Yan [ Information Engineering School, Yulin University, Yulin 719000, Shaanxi, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605