Earticle

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

Abstract
 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

키워드

저자

• Qihua Liu [ High Level Engineering Research Center of Electronic-Commerce, Jiangxi Provincial Colleges and Universities School of Information Technology, Jiangxi University of Finance and Economics ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605