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基于加权借阅网络的个性化推荐算法与实现

  • 袁虎声 ,
  • 赵洗尘
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  • 深圳大学城图书馆 深圳 518055
袁虎声(ORCID:0000-0003-2479-2076),系统网络部主任,高级工程师,硕士

收稿日期: 2015-12-30

  修回日期: 2016-04-18

  网络出版日期: 2016-05-20

Personalized Recommendation Algorithm Based on Weighted Book-borrowing Network and Its Realization

  • Yuan Husheng ,
  • Zhao Xichen
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  • University Town Library of Shenzhen, Shenzhen 518055

Received date: 2015-12-30

  Revised date: 2016-04-18

  Online published: 2016-05-20

摘要

[目的/意义] 在应用大数据提升图书馆服务的背景下,为提高借阅推荐的有效性,设计一种基于加权借阅网络的个性化推荐算法。[方法/过程] 引入复杂网络理论的分析方法,以深圳大学城图书馆的实际借阅数据为例,证明借阅网络具有二分图特性和BA无标度网络特性,具备个性化推荐的条件;通过构建读者借阅子网,采用能量传递六步法,实现个性化图书借阅推荐。[结果/结论] 实际借阅数据的验证结果表明,算法是有效且具有实际应用意义的。

本文引用格式

袁虎声 , 赵洗尘 . 基于加权借阅网络的个性化推荐算法与实现[J]. 图书情报工作, 2016 , 60(10) : 130 -134 . DOI: 10.13266/j.issn.0252-3116.2016.10.018

Abstract

[Purpose/significance] Under the background of improving library service with big data, in order to increase the effectiveness of borrowing recommendation, this paper designs a personalized recommendation algorithm based on weighted book-borrowing network.[Method/process] It introduces the analysis method of complex network theory. Then it takes the actual borrowing data of University Town of Shenzhen for example, proves that borrowing network has the characteristics of bipartite graph and BA scale-free network and has the condition of personalized recommendation. Finally, it takes energy transfer program to realize the personalized library recommendation.[Result/conclusion] The verification result of actual borrowing data shows that the algorithm is effective and has practical significance.

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