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New Technology of Library and Information Service  2010, Vol. 26 Issue (12): 64-69    DOI: 10.11925/infotech.1003-3513.2010.12.11
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Application of Knowledge Discovery Based on Wanfang Data (2003-2007)
Xie Jing, Jiang Lan, Wang Dongbo, Su Xinning
Department of Information Management, Nanjing University, Nanjing 210093,China
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Abstract  

The paper makes an association analysis on authors, affiliations and documents based on the data of the papers published in Chinese periodicals from Wanfang Data(2003-2007). This helps to indicate the latent relationships among authors, affiliations and documents. An effective method of entity recognition is also proposed to improve the accuracy of association analysis in this application. And the application is supposed to be the basis of further semantic retrieval.

Key wordsKnowledge      discovery      Wanfang      data      Entity      recognition      Similarity      computation     
Received: 28 September 2010      Published: 07 January 2011
: 

TP391

 

Cite this article:

Xie Jing, Jiang Lan, Wang Dongbo, Su Xinning. Application of Knowledge Discovery Based on Wanfang Data (2003-2007). New Technology of Library and Information Service, 2010, 26(12): 64-69.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.12.11     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2010/V26/I12/64


[1] 张晓林.走向知识服务:寻找新世纪图书情报工作的生长点
[J]. 中国图书馆学报,2000,26(5):32-37.

[2] 姜永常.论知识服务与信息服务
[J]. 情报学报,2001,20(5):572-578.

[3] 李晓鹏,颜端武,陈祖香.国内外知识服务研究现状、趋势与主要学术观点
[J]. 图书情报工作,2010,54(6):107-111.

[4] Blair D C, Maron M E. An Evaluation of Retrieval Effectiveness for a Full-text Document-retrieval System
[J]. Communications of the ACM, 1985, 28(3):289-299.

[5] Chen H, Lynch K J. Automatic Construction of Networks of Concepts Characterizing Document Databases
[J]. IEEE Transactions on Systems, Man and Cybernetics, 1992, 22(5), 885-902.

[6] Chen H, Lynch K J, Basu K, et al. Generating Integrating, and Activating Thesauri for Concept-based Document Retrieval
[J]. IEEE Expert, 1993, 8(2):25-34.

[7] Berry M W, Dumais S T, O’Brien G W. Using Linear Algebra for Intelligent Information Retrieval
[J]. SIAM Review, 1995, 37(4):573-595.

[8] Hofmann T. Probabilistic Latent Semantic Indexing.In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Berkeley, California, United States. New York:ACM,1999:50-57.

[9] Cai D, Mei Q, Han J, et al. Modeling Hidden Topics on Document Manifold. In: Proceeding of the 17th ACM Conference on Information and Knowledge Management, Napa Valley, California, USA. New York:ACM,2008:911-920.

[10] Xie F, Liu X, Hu Q. Comparison Probabilistic Latent Semantic Indexing Model in Chinese Information Retrieval. In: Proceedings of the 2009 International Forum on Information Technology and Applications, Chengdu, China.2009:559-562.

[11] Scopus. Search for Author. http://www.scopus.com/search/form/authorFreeLookup.url.

[12] Open Researcher & Contributor ID(ORCID). http://www.orcid.org/.

[13] 裴雷,马费成.社会网络分析在情报学中的应用和发展
[J]. 图书馆论坛,2006,26(6):40-45.

[14] 朱庆华,李亮.社会网络分析法及其在情报学中的应用
[J]. 情报理论与实践,2008,31(2):179-183,174.

[15] 王锐兵,许有志,王道平.基于语义扩展的知识服务检索与组合方法研究
[J]. 情报杂志,2008(12):40-42.

[16] DBLP Bibliography. http://www.informatik.uni-trier.de/%7Eley/db/.

[17] 中国人民大学网络与移动数据管理实验室. 学术空间ScholarSpace(C-DBLP). http://www.cdblp.cn.

[18] 中国科学院计算技术研究所. ICTCLAS资源. http://ictclas.org/Down_OpenSrc.asp.

[19] 陈克利,宗成庆,王霞.基于大规模真实文本的平衡语料分析与文本分类方法.见: 全国第七届计算语言学联合学术会议,哈尔滨.北京:清华大学出版社,2003:540-545.

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