Please wait a minute...
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
article Current Issue | Archive | Adv Search |
Data Mining of Subject Words for Bibliographic Database in Small and Medium-sized Libraries Based on FP-tree
Chen AiyingQin Zongrong2
1(Guangzhou Maritime College Library, Guangzhou 510725,China)
2(Department of Computer and Information Engineering,Guangzhou Maritime College,Guangzhou 510725, China)
Download: PDF(1358 KB)   HTML  
Export: BibTeX | EndNote (RIS)      
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 wordsAssociation 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
About author:: Chen Aiying Qin Zongrong

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.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.07-08.20     OR     http://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.

[1] Yong Zhang,Shuqing Li,Yongshang Cheng. Mining Algorithm for Weighted Association Rules Based on Frequency Effective Length[J]. 数据分析与知识发现, 2019, 3(7): 85-93.
[2] Quan Lu,Anqi Zhu,Jiyue Zhang,Jing Chen. Research on User Information Requirement in Chinese Network Health Community: Taking Tumor-forum Data of Qiuyi as an Example[J]. 数据分析与知识发现, 2019, 3(4): 22-32.
[3] Dongmei Mu,Hui Fa,Ping Wang,Jing Sun. Research on Disease Risk Factors on Structural Equation Model[J]. 数据分析与知识发现, 2019, 3(4): 80-89.
[4] Yongnan Li. Using Bayes Theory to Classify Counter Terrorism Intelligence[J]. 数据分析与知识发现, 2018, 2(10): 9-14.
[5] Dongmei Mu,Ping Wang,Danning Zhao. Reducing Data Dimension of Electronic Medical Records: An Empirical Study[J]. 数据分析与知识发现, 2018, 2(1): 88-98.
[6] Zhongyi Hu,Chaoqun Wang,Jiang Wu. Identifying Phishing Websites with Multiple Online Data Sources[J]. 数据分析与知识发现, 2017, 1(6): 47-55.
[7] Siwei Jiang,Zhenping Xie,Meijie Chen,Ming Cai. Self-Explainable Reduction Method for Mixed Feature Data Modeling[J]. 数据分析与知识发现, 2017, 1(12): 92-100.
[8] Xing Wei,Dehua Hu,Minhan Yi,Qizhen Zhu,Wenjie Zhu. Extracting Disease-Gene-Drug Correlations Based on Data Cube[J]. 数据分析与知识发现, 2017, 1(10): 94-104.
[9] Mu Dongmei,Ren Ke. Discovering Knowledge from Electronic Medical Records with Three Data Mining Algorithms[J]. 现代图书情报技术, 2016, 32(6): 102-109.
[10] Li Feng,Li Shu’ning,Yu Jing. A Department Oriented Library Usage Data System for Graduates[J]. 现代图书情报技术, 2016, 32(5): 99-103.
[11] Guangce Ruan, Lei Xia. Mining Document Topics Based on Association Rules[J]. 数据分析与知识发现, 2016, 32(12): 50-56.
[12] Du Siqi, Li Honglian, Lv Xueqiang. Research of Chinese Chunk Parsing in Application of the Product Feature Extraction[J]. 现代图书情报技术, 2015, 31(9): 26-30.
[13] Zhao Jingxian. Detect of Internet Fake Public Opinion Based on Decision Tree[J]. 现代图书情报技术, 2015, 31(6): 78-84.
[14] He Jianmin, Wang Zhe. The Pedigree Method to Mine Influential Clusters of Topic Information in Social Network[J]. 现代图书情报技术, 2015, 31(5): 65-72.
[15] Huang Wenbin, Xu Shanchuan, Ma Long, Wang Jun. Analysis of Mobile User Behaviors with Telecommunication Data[J]. 现代图书情报技术, 2015, 31(5): 80-87.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn