Earticle

초록

영어

Recommender systems are now popular both commercially and in the research community, where many approaches have been suggested for providing recommendations. However, evaluating the affectivity of recommender systems is a challenging problem and most of the approaches used for evaluation are based on using some sort of a dataset. This paper describes a method for measuring the accuracy of a collaborative filtering based recommender systems called “User-Advertisement Simulation” that utilizes a simulation approach that creates artificial users and advertisements of a virtual market, then measures accuracy of the products’ ranking based on the user’s profile.

목차

Abstract
 1. Introduction
 2. Overview of the User-Advertisement Simulation
 3. Architecture of The User-Advertisement simulation
  3.1. Optimization Parameter
  3.2. Meeting’s Room
  3.3. Feedback Generator
 4. Results
 5. Discussion and Conclusion
 References

키워드

저자

• Niki Shakeri [ Dept. of Computer Science, Lakehead University, Thunder Bay, ON, Canada ]
• Jinan Fiaidhi [ Dept. of Computer Science, Lakehead University, Thunder Bay, ON, Canada ]
• Sabah Mohammed [ Dept. of Computer Science, Lakehead University, Thunder Bay, ON, Canada ]
• Tia-hoon Kim [ Department of Convergence Security, Sungshin W. University, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605