원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.9 No.10
2016.10
pp.75-86
피인용수 : 0건 (자료제공 : 네이버학술정보)
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보