Bipartite network projection and personal recommendation

被引：0
|
作者：
Zhou, Tao [1 ,2 ,3 ]
Ren, Jie [1 ]
Medo, Matus [1 ]
Zhang, Yi-Cheng [1 ,4 ]
机构：
[1] Univ Fribourg, Dept Phys, Chemin Muse 3, CH-1700 Fribourg, Switzerland
[2] Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Anhui, Peoples R China
[3] Univ Sci & Technol China, Nonlinear Sci Ctr, Hefei 230026, Anhui, Peoples R China
[4] Univ Elect Sci & Technol China, Management Sch, Lab Informat Econ & Internet Res, Chengdu 610054, Sichuan, Peoples R China
来源：
2011 INTERNATIONAL CONFERENCE ON APPLIED SOCIAL SCIENCE (ICASS 2011), VOL III | 2011年
关键词：
Book Recommendation; Recommendation Algorithm; Personalized Service; Borrowing History Records; Bipartite Network;
D O I：
暂无
中图分类号：
C [社会科学总论];
学科分类号：
03 ; 0303 ;
摘要：
In this paper, we propose a book recommendation system which can offer personalized services by mining the data of readers' borrowing history records and modeling the relationships among readers and books as a bipartite network. With the development of digital library, personalized services to the readers are demanded and feasible. The electronic borrowing history records can be generated and accessed as the automatic integrated library systems are widely used. Based on this data, a bipartite network can be constructed, in which readers and books are two kinds of nodes and borrowing indicates a link between two nodes. An effective personal recommendation algorithm has been proposed based on a weighted projection of this kind of user-object network. We argue when this algorithm is incorporated into the digital library system, it has many overwhelming advantages in personalized services of book recommendations.
引用
收藏
页码：489 / +
页数：2
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