Earticle

초록

영어

Under the conditions of different community formation, this paper proposed two different models of formation communities. Firstly, we put forward two kinds of similarity calculation models, and compare them with the traditional similarity model, Secondly, several similarity models are tested under different conditions of community formation. Finally it compares tow models of forming communities and finds that for non-strict division of community model has a higher accuracy and diversity of recommendation, compared with the strict division of community model. Thus, the experiments show that the non-strictly divided communities’ model is more suitable for recommendation system, especially for the personalized recommendation.

목차

Abstract
 1. Introduction
 2. Recommendation Algorithm Based on Community Relationship in Network
  2.1. Improved Equation of User Similarity
  2.2. Forming Process of Community
 3. Experiment Design and Discussion
  3.1 Experimental Dataset
  3.2 Evaluation of the Effect of Recommendation
  3.3. Recommendation Result Test
 4. Conclusion
 References

키워드

저자

• Dong Liang [ Qiongtai Teachers College, Haikou 570100, china ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605