Earticle

초록

영어

Aiming at the problem that the traditional Collaborative Filtering algorithm has low recommendation accuracy, in the paper, we propose a collaborative filtering recommendation algorithm based on the global trust degree integrating the direct trust information in the social networks. We first transform the local trust relationships to the global trust relationship by the rules in the trust network, and get the trust rank of all users in the trust networks; Then we use the global trust value to instead of the similarity information value as the weights of a predicted formula in the traditional collaborative recommendation algorithm, and integrate the weights to the matrix factorization-based recommendation model.

목차

Abstract
 1. Introduction
 2. Matrix Decomposition CF (Collaborative Filtering) Algorithm based on Global Confidence Degree
  2.1. Recommendation Model
  2.2. Basic Steps
  2.3. The Algorithm Description
 3. Experimental Analysis and Results
  3.1. Experiment Data Set
  3.2. Test Environment Configuration
  3.3. Evaluation Index in the Experiment
  3.4. Validation of Collaborative Filtering Recommendation Algorithm based on Global Confidence Degree
 4. Conclusion
 References

키워드

저자

• Qi Zheng [ School of Computer Science and Engineering, Jilin Jianzhu University, Changchun 130000, 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