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New Technology of Library and Information Service  2010, Vol. 26 Issue (7/8): 114-119    DOI: 10.11925/infotech.1003-3513.2010.07-08.20
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Data Mining of Subject Words for Bibliographic Database in Small and Medium-sized Libraries Based on FP-tree
Chen Aiying1  Qin Zongrong2
1（Guangzhou Maritime College Library, Guangzhou 510725,China）
2(Department of Computer and Information Engineering，Guangzhou Maritime College,Guangzhou 510725, China)
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Abstract  

For ubiquitous subject indexing problem of Chinese books in small and medium-sized libraries, this paper uses the FP-growth algorithm to mine discipline subject field, and the discipline thesaurus of each category is obtained. The reference basis for making machine-readable data subject indexing rules and bylaws of Chinese books in small and medium-sized libraries is provided as well as subject indexing of Chinese books.
Key words： Association rules      Data mining      FP-growth algorithm      Discipline subject      Minimum support     
Received: 25 May 2010      Published: 19 September 2010
: 

G250 

 
  TP391

 		 
Corresponding Authors: Chen Aiying     E-mail: cay6932@163.com
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Cite this article:

Chen Aiying Qin Zongrong. Data Mining of Subject Words for Bibliographic Database in Small and Medium-sized Libraries Based on FP-tree. New Technology of Library and Information Service, 2010, 26(7/8): 114-119.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.07-08.20     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2010/V26/I7/8/114

［1］ 赵伯兴. 论网络环境下书目质量理念的拓变［J］.图书馆建设，2006（6）：44-47.
［2］ 符勤. 通过编目技术提升在线书目的质量［J］.图书馆，2007（3）：74-76,95.
［3］ Han J, Pei J,Yin Y．Mining Frequent Patterns Without Candidate Generation［J］.Data Mining and Knowledge Discovery,2004（8）：53-87.
［4］ 牛根义. 国内图书馆数据挖掘研究［J］.现代情报，2009,29（1）：128-130,133.
［5］ 陈耀盛.网络信息组织［M］.北京：科学技术文献出版社，2004：200.
［6］ 章华. 江苏高校图书馆编目数据存在的问题及对策［J］.图书馆建设，2008（7）：75-77.
［7］ 董素音，冯宝秀.现代图书馆藏书建设工作［M］.北京：海洋出版社，2006：108-109.
［8］ 王怀汀. 金盘图书馆集成管理系统的总体设计［J］.现代图书情报技术，1997（1）：34-37.
［9］ 詹萌. 我国图书馆书目数据库的数据特征分析与检索方式扩展研究［J］.图书情报工作，2006,50（7）：68-72.
［10］ 国家图书馆《中国图书馆分类法》编辑委员会．中国分类主题词表（第二版）分类号—主题词对应表（一）［M］．北京：北京图书馆出版社，2005：22-25.
［11］ 郭伟,叶德谦. 改进的基于FP-tree的频繁项集挖掘算法［J］. 计算机工程与应用，2007,43(19)：174-176.
［12］ 车传辉，倪明. FP算法在企业信息类隐性知识挖掘中的应用研究［J］.情报杂志，2009，28（4）：144-146,55.
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