원문정보
초록
영어
Recommender systems are a critical component of e-commerce websites. Considering the users’ complete spectrum of interests, the limitation of current research on recommender systems lies in that they have only paid attention to improving the accuracy of recommendation algorithms while neglected the diversification of recommendations. In this paper, we integrated a user preference matching algorithm based on communities of interests and a diverse information recommendation algorithm based on trustable neighbors to develop a hybrid information recommendation model that allows for both accuracy and diversity. Results of experiment and evaluation indicated this model can increase the diversity of recommendations with only a minimal accuracy loss.
목차
1. Introduction
2. Literature Review
3. Construction of Multi-Hierarchical Communities of Interest
3.1. HUNC-based Construction of user Interest Ontology
3.2. Multi-hierarchical Semantic Communities of Interest based on User Interest Ontology
4. Hybrid Recommendation based on Communities of Interest and Trustable Neighbors
4.1. User Preference Matching Algorithm based on Communities of Interest
4.2. Diverse Information Recommendation Algorithm based on Trustable Neighbors
5. Experiments
6. Conclusion and Discussion
ACKNOWLEDGEMENTS
References