Earticle

초록

영어

Recently, with the rapid development of science and cultural areas, the written and electronic amount of books in the university libraries increases sharply. When readers use the traditional searching system which is based on the collaborative filtering method, it is usually difficult for them to find out their interested books due to a large number of results from the system. Aiming at this problem, the paper points out a sort of personalized recommending system. This system optimizes the collaborative filtering method based on the information of the users, uses the new collaborative filtering method based on the classification of users and books, and analyzes and orders a variety of recommending information after filter. From the experiment, it concludes that compared with the traditional recommending system the personalized system targets towards different types of readers. The numbers of books which feed back to readers have decreased a lot. What’s more, after a comprehensive analysis and order of the various recommending information, the average recommending accuracy will make further improvement.

목차

Abstract
 1. Introduction
 2. Recommendation based on the Collaborative Filter
 3. Personalized Recommending System
  3.1 The Users’ Information Model
  3.2 The Personalized Recommending Model
  3.3 The Comprehensive Order of the Recommending Results
 4. The Experiment and Analysis of the Results
  4.1. The Preparation of the Experiment Statistics
  4.2. The Evaluating Standard of the Experiment
  4.3. The Experiment Results and Analysis
 5. Conclusion
 References

키워드

저자

• Jihong Wei [ College of Civil Engineering and Architecture, Harbin University of Science and Technology, Harbin, 150080, 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