Earticle

초록

영어

As an effective recommendation technology to solve "information overload" problem, collaborative filtering has widly attracted attention of scholars from various fields. First, this paper proposes a method for measuring the recommending ability of user based on popularity and long-tailed distribution. Then, a global core user set is constructed for recommadition based on the recommending ability and samples selection idea in data mining, aimming to take advantage of users in the different part of the long tail distribution and reduce computing complexity of the algorithm without lowing the recommended performance. Experimental results show that the algorithm is effective and can be used to solve the real-time problem and cold start recommendation.

목차

Abstract
 1. Introduction
 2. Literature Review
 3. Frequency of the Rated Items
 4. The Method of Constructing the Core User Subset
 5. Experiments
  5.1. Evaluation Metrics
  5.2. Experimental Results and Analysis
 6.Conclusions
 Acknowledgments
 References

키워드

저자

• Zhang Li [ School of Information Technology & Management Engineering,University of International Business and Economics, Beijing,100029,China ]
• Yu Lei [ School of Information Technology & Management Engineering,University of International Business and Economics, Beijing,100029,China ]
• Cao Shuyan [ School of Information Technology & Management Engineering,University of International Business and Economics, Beijing,100029,China ]

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