Earticle

초록

영어

To ameliorate the limitations of traditional collaborative filtering technologies and enhance the recommendation quality of agricultural science and technology information, a collaborative filtering recommendation method based on synthetic strategy is proposed. Firstly, filter the user set and user-item rating matrix according to the location of target user, which can solve the regional problem. Then, predict ratings of items according to the similarity of users or item content, which can relax the impact of the sparse rating. In addition, add the rating time to the user-item rating matrix to distinguish the timeliness of the user preference, and add user preference shifting in the similarity formula as a factor which can express the similarity of users or item content better. Our method can not only guarantee the recommended information is local and suit to current season of agricultural production, but also ensure the recommending precision under sparse rating data.

목차

Abstract
 1. Introduction
 2. Definitions and Symbols
 3. Period Based User Preference and User Preference Shifting
 4. User Based Rating Prediction
 5. Item Content Based Rating Prediction
 6. Collaborative Filtering Recommendation Algorithm Basing onComprehensive Strategies for Agricultural Science and Technology Information
 7. Experiment
 8. Conclusion
 Acknowledgments
 References

키워드

저자

• Song Jinling [ Hebei Normal University of Science & Technology, Qinhuangdao 066004, China ]
• Huang Liming [ Hebei Normal University of Science & Technology, Qinhuangdao 066004, China ]
• Gao Yan [ Liaoning Institute of Science and Technology Benxi 117004, China ]
• Liu Aiyong [ Hebei Normal University of Science & Technology, Qinhuangdao 066004, China ]
• Liu Haibin [ Hebei Normal University of Science & Technology, Qinhuangdao 066004, 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