Please wait a minute...
New Technology of Library and Information Service  2014, Vol. 30 Issue (9): 1-7    DOI: 10.11925/infotech.1003-3513.2014.09.01
Current Issue | Archive | Adv Search |
Research on Automatic Classification of Chinese Books Based on Social Tagging
He Lin1, Wan Jian2, He Juan1, Guo Shiyun1
1. College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China;
2. College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China
Export: BibTeX | EndNote (RIS)      

[Objective] The paper aims to improve the ability of automatic text classification of social tagging by controlling the relation and quality of social tagging. [Methods] A classification model called “core controlled, shell uncontrolled” is constructed based on the control of a concept space called Social tagging-Keyword in order to realize the regulation control of social tagging based on subject headings. [Results] The validity tests show that this new method has a better performance on the text classification based on social tagging in consideration of efficiency and the cost. [Limitations] The data used for concept space is not as much as possible due to the restriction of the Website. Also, the concept space is lack of deep semantic relations which would be richer in the future. [Conclusions] This study proposes a feasible solution for improving the quality of social tags and the capacity of automatic text classification.

Key wordsSocial tagging      Chinese books      Concept space      Dependence mapping      Automatic classification     
Received: 01 April 2014      Published: 20 October 2014
:  G250.73  

Cite this article:

He Lin, Wan Jian, He Juan, Guo Shiyun. Research on Automatic Classification of Chinese Books Based on Social Tagging. New Technology of Library and Information Service, 2014, 30(9): 1-7.

URL:     OR

[1] 曹高辉, 焦玉英, 成全. 基于凝聚式层次聚类算法的标签聚类研究[J]. 现代图书情报技术, 2008(4): 23-28. (Cao Gaohui, Jiao Yuying, Cheng Quan. Research on Tag Cluster Based on Hierarchical Agglomerative Clustering Algorithm [J]. New Technology of Library and Information Service, 2008(4): 23-28.)
[2] Begelman G, Keller P, Smadja F. Automated Tag Clustering: Improving Search and Exploration in the Tag Space[OL]. [2012-12-16].
[3] Heymann P, Garcia-Molinay H. Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems[OL]. [2012-12-16]. 775/1/2006-10.pdf.
[4] Christiaens S. Metadata Mechanisms: From Ontology to Folksonomy and Back [A]//On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshop [C]. Berlin: Springer, 2006(4277): 199-207.
[5] 易明, 王学东, 邓卫华. 基于社会网络分析的社会化标签网络分析与个性化信息服务研究[J]. 中国图书馆学报, 2010, 36(2): 107-114. (Yi Ming, Wang Xuedong, Deng Weihua. Social Tagging Network Analysis and Personalized Information Service Based on Social Network Analysis[J]. Journal of Library Science in China, 2010, 36(2): 107-114.)
[6] 李亚婷, 马费成. 基于标签共现的社会网络分析研究[J]. 情报杂志, 2012, 31(7): 103-109. (Li Yating, Ma Feicheng. Social Network Analysis Based on Tags Co-occurrence[J]. Journal of Intelligence, 2012, 31(7): 103-109.)
[7] 任家乐, 雷若寒, 姜晓. OPAC与“美味书签”相结合的学术资源导航系统构建探索[J]. 图书馆杂志, 2010, 29(6): 21-24, 20. (Ren Jiale, Lei Ruohan, Jiang Xiao. Integrating OPAC with Delicious: A New Guidance System for Academic Resources [J]. Library Journal, 2010, 29(6): 21-24, 20.)
[8] Quintarelli E, Resmini A, Rosati L. FaceTag: Integrating Bottom-up and Top-down Classification in a Social Tagging System [OL]. [2014-02-25]. QuintarelliEtc.pdf.
[9] Munk T B, Mork K. Folksonomy: The Power Law the Significance of the Least Effort [J]. Knowledge Organization, 2007, 34(1): 16-33.
[10] Berendt B, Hanser C. Tags are Not Metadata, but “Just More Content”- to Some People [EB/OL]. [2013-12-03]. http://
[11] Sun A, Suryanto M A, Liu Y. Blog Classification Using Tags: An Empirical Study [C]. In: Proceedings of the 10th International Conference on Asian Digital Libraries. Berlin, Germany: Springer, 2007: 307-316.
[12] Razikin K, Goh D H L, Chua A Y K, et al. Can Social Tags Help You Find What You Want? [C]. In: Proceedings of the 12th European Conference on Digital Libraries (ECDL 2008). Berlin: Springer, 2008: 50-61.
[13] 丛鲁丽. 基于大众分类法的中文博客分类方法[J]. 情报杂志, 2009, 28(9): 50-52. (Cong Luli. Chinese Weblog Pages Classification Based on Folksonomy [J]. Journal of Intelligence, 2009, 28(9): 50-52.)
[14] 李劲, 张华, 吴浩雄, 等. 基于社会标注质量的文本分类模型框架[J]. 计算机应用, 2012, 32(5): 1335-1339. (Li Jin, Zhang Hua, Wu Haoxiong, et al. Text Classification Model Framework Based on Social Annotation Quality [J]. Journal of Computer Applications, 2012, 32(5): 1335-1339.)
[15] 马张华, 侯汉清. 文献分类法主题法导论[M]. 北京: 北京图书馆出版社, 1999: 153-155. (Ma Zhanghua, Hou Hanqing. Introduction to Literature Classification Act Themes [M]. Beijing: Beijing Library Press, 1999: 153-155.)
[16] Sahon G. Mathematics and Information Retrieval [J]. Journal of Documentation, 1979, 35(1): 1-29.

[1] Xiong Huixiang,Li Xiaomin,Li Yueyan. Group Recommendation Based on Attribute Mining of Book Reviews[J]. 数据分析与知识发现, 2020, 4(2/3): 214-222.
[2] Gong Lijuan,Wang Hao,Zhang Zixuan,Zhu Liping. Reducing Dimensions of Custom Declaration Texts with Word2Vec[J]. 数据分析与知识发现, 2020, 4(2/3): 89-100.
[3] Li Jiao,Huang Yongwen,Luo Tingting,Zhao Ruixue,Xian Guojian. Automatic Classification Method Based on Multi-factor Algorithm[J]. 数据分析与知识发现, 2020, 4(11): 43-51.
[4] Deng Sanhong,Fu Yuyangzi,Wang Hao. Multi-Label Classification of Chinese Books with LSTM Model[J]. 数据分析与知识发现, 2017, 1(7): 52-60.
[5] Xiong Huixiang,Jiang Wuxuan. Clustering and Recommending Users Based on Tags and Relation Network[J]. 数据分析与知识发现, 2017, 1(6): 36-46.
[6] Xie Mengyao,Pan Xuwei. Constructing Dynamic Social Tag Cloud for User Interests[J]. 数据分析与知识发现, 2017, 1(2): 35-40.
[7] Li Xiangdong,Ba Zhichao,Gao Fan. Review of Digital Documents Automatic Classification Research[J]. 现代图书情报技术, 2016, 32(9): 17-26.
[8] Zhao Yan, Wang Yamin. Model for Personalized Recommendation Based on Social Tagging in P2P Environment[J]. 现代图书情报技术, 2014, 30(5): 50-57.
[9] Hu Bing, Zhang Jianli. Research on Chinese Patent Automatic Classification Method Based on Statistical Distribution[J]. 现代图书情报技术, 2013, 29(7/8): 101-106.
[10] He Jinjing, Dou Yongxiang. Overview on Construction of Ontology in Social Tagging System[J]. 现代图书情报技术, 2013, (6): 16-22.
[11] Gao Bin. An Exploratory Study of Users and Tags on Social Bookmarking Websites[J]. 现代图书情报技术, 2012, 28(6): 65-71.
[12] Xu Jian, Wen Haosheng. Study on Talents Description Web Page Automatic Recognition System[J]. 现代图书情报技术, 2011, 27(6): 20-26.
[13] Ma Fang. Research of Patent Automatic Classification Based on RBFNN[J]. 现代图书情报技术, 2011, 27(12): 58-63.
[14] Wang Song,Dai Yisheng,Li Baozhen. Explore Network Resource Topics from Social Annotations System Based on PLSA[J]. 现代图书情报技术, 2010, 26(3): 47-51.
[15] Li Junlian, Li Danya, Huang Lihui, Sun Haixia, Ji Yujing, Wang Qian. Research on Chinese Medical Concept Space Based on Word Co-occurrence[J]. 现代图书情报技术, 2010, 26(11): 59-63.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938