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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (8): 88-97    DOI: 10.11925/infotech.2096-3467.2018.0178
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Matching Strategies for Institution Names in Literature Database
Haixia Sun1,2,Lei Wang2,Yingjie Wu2,Weina Hua1,Junlian Li2()
1School of Information Management, Nanjing University, Nanjing 210093, China
2Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, China
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Abstract  

[Objective] This paper designs and implements matching strategies for institution names in literature database, aiming to regulate their storage and management. [Methods] We first established seven name matching rules based on their regions, types and naming characteristics. Then, we designed four hybrid matching strategies combining rules and Levenstein distance. Finally, we evaluated the four hybrid strategies with institution names from the papers indexed by Chinese Biomedical Literature (CBM) database during 2006-2011. [Results] More than six million affiliation strings from CBM were matched, which included higher education institutions, hospitals and research institutes. We found that the hybrid matching strategy based on region, naming characteristics and Levenstein distance obtained the highest precision (all above 80%), recall (64.82%), and F-value (71.66%). [Limitations] The rules and related dictionary were mainly constructed with human experience and their coverage is limited. There are some errors in the identifying institution names. The proposed strategy cannot address the issues caused by the transformative actions of institutions. [Conclusions] The proposed strategies could improve the performance of scientific research literature databases.

Key wordsInformation Retrieval      Normalization of Affiliation Strings      Similarity Measure      Hybrid Strategy      Literature Database     
Received: 11 February 2018      Published: 08 September 2018

Cite this article:

Haixia Sun,Lei Wang,Yingjie Wu,Weina Hua,Junlian Li. Matching Strategies for Institution Names in Literature Database. Data Analysis and Knowledge Discovery, 2018, 2(8): 88-97.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0178     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I8/88

[1] Khalid M A, Jijkoun V, De Rijke M.The Impact of Named Entity Normalization on Information Retrieval for Question Answering[C]//Proceeding of the IR Research, 30th European Conference on Advances in Information Retrieval,Glasgow, UK. Berlin, Heidelberg: Springer-Verlag, 2008: 705-710.
[2] 唐金玲. 国际三大检索系统论文作者机构名称问题研究——以高校机构名称为例[J]. 情报探索, 2014(9): 80-84.
[2] (Tang Jinling.Study on Issues of Author Affiliations on Papers Included in International Three Key Retrieval Systems: Case Study of Name of University[J]. Information Research, 2014(9): 80-84.)
[3] 苏新宁. 图书馆、情报与文献学学术影响力研究报告(2000-2004)——基于CSSCI的分析[J]. 情报学报, 2006, 25(2): 131-153.
[3] (Su Xinning.Report on Academic Influence in Library, Information and Documentation Science (2000-2004)[J]. Journal of the China Society for Scientific and Technical Information, 2006, 25(2): 131-153.)
[4] 曾建勋, 王立学. 面向知识评价的规范文档建设方法[J]. 图书情报工作, 2012, 56(10): 101-106.
[4] (Zeng Jianxun, Wang Lixue.Construction of Knowledge Evaluation-oriented Authority Files[J]. Library and Information Service, 2012, 56(10): 101-106.)
[5] Abramo G, D’Angelo C A, Pugini F. The Measurement of Italian Universities’ Research Productivity by a Non Parametric-Bibliometric Methodology[J]. Scientometrics, 2008, 76(2): 225-244.
[6] French J C, Powell A L, Schulman E.Automating the Construction of Authority Files in Digital Libraries: A Case Study[C]//Proceedings of International Conference on Theory and Practice of Digital Libraries.Berlin,Heidelberg: Springer, 1997: 55-71.
[7] Liu W L, Doğan R I, Sun K, et al.Author Name Disambiguation for PubMed[J]. Journal of the Association for Information Science and Technology, 2014, 65(4): 765-781.
[8] 孙海霞, 李军莲. 学术论文作者机构规范文档构建[J]. 医学信息学杂志, 2015, 36(11): 42-47.
[8] (Sun Haixia, Li Junlian.Construction of Authority File of Author Affiliations[J]. Journal of Medical Informatics, 2015, 36(11): 42-47.)
[9] 陈金星, 祝忠明. 责任者名称规范控制研究及进展[J]. 现代图书情报技术, 2009(12): 12-17.
[9] (Chen Jinxing, Zhu Zhongming.Research Progress of the Name Authority Control for the Contributor[J]. New Technology of Library and Information Service, 2009(12): 12-17.)
[10] Jonnalagadda S R, Topham P.NEMO: Extraction and Normalization of Organization Names from PubMed Affiliation String[J]. Journal of Biomedical Discovery and Collaboration, 2010, 5(1): 50-75.
[11] Jiang Y, Zheng H T, Wang X, et al.Affiliation Disambiguation for Constructing Semantic Digital Libraries[J]. Journal of the American Society for Information Science and Technology, 2011, 62(6): 1029-1041.
[12] Torvik V I, Weeber M, Swanson D R, et al.A Probabilistic Similarity Metric for Medline Records: A Model for Author Name Disambiguation[J]. Journal of the American Society for Information Science and Technology, 2005, 56(2): 140-158.
[13] Cuxac P, Lamirel J C, Bonvallot V.Efficient Supervised and Semi-Supervised Approaches for Affiliations Disambiguation[J]. Scientometrics, 2013, 97(1): 47-58.
[14] French J C, Powell A L, Schulman E.Using Clustering Strategies for Creating Authority Files[J]. Journal of the American Society for Information Science, 2000, 51(8): 774-786.
[15] Huang S, Yang B, Yan S, et al.Institution Name Disambiguation for Research Assessment[J]. Scientometrics, 2014, 99(3): 823-838.
[16] 孙海霞, 成颖. 信息集成中的字符串匹配技术研究[J]. 现代图书情报技术, 2007(7): 22-26.
[16] (Sun Haixia, Cheng Ying.Study on String-based Matching of Information Intergration[J]. New Technology of Library and Information Service, 2007(7): 22-26.)
[17] Jacob F, Javed F, Zhao M, et al.sCooL: A System for Academic Institution Name Normalization[C]//Proceeding of 2014 International Conference on Collaboration Technologies & Systems.IEEE, 2014: 86-93.
[18] Bollegala D, Ishizuka M, Matsuo Y.Measuring Ssemantic Similarity Between Words Using Web Search Engines[C]// Proceeding of the 14th International Conference on World Wide Web. 2007: 757-766.
[19] Aumüller D, Rahm E.Web-based Affiliation Matching[C]// Proceeding of International Conference on Information Quality. DBLP, 2009: 246-256.
[20] 杨波, 杨军威, 阎素兰. 基于规则的机构名称规范化研究[J]. 现代图书情报技术, 2015(6): 57-63.
[20] (Yang Bo, Yang Junwei, Yan Sulan.Research on Rule-based Normalization of Institution Name[J]. New Technology of Library and Information Service, 2015(6): 57-63.)
[21] Onodera N, Iwasawa M, Midorikawa N, et al.A Method for Eliminating Articles by Homonymous Authors from the Large Number of Articles Retrieved by Author Search[J]. Journal of the American Society for Information Science and Technology, 2011, 62(4): 677-690.
[22] 张小衡, 王玲玲. 中文机构名称的识别与分析[J]. 中文信息学报, 1997, 11(4): 21-32.
[22] (Zhang Xiaoheng, Wang Lingling.Identification and Analysis of Chinese Organization and Institution Names[J]. Journal of Chinese Information Processing, 1997, 11(4): 21-32.)
[23] 中国生物医学文献数据库[EB/OL]. [2017-10-30]. .
[23] (SinoMed[EB/OL]. [2017-10-30].
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