IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v69y2006i2d10.1007_s11192-006-0156-3.html
   My bibliography  Save this article

The unification of institutional addresses applying parametrized finite-state graphs (P-FSG)

Author

Listed:
  • Carmen Galvez

    (Scimago Research Group, Department of Information Science,University of Granada)

  • Félix Moya-Anegón

    (Scimago Research Group, Department of Information Science,University of Granada)

Abstract

Summary We propose a semi-automatic method based on finite-state techniques for the unification of corporate source data, with potential applications for bibliometric purposes. Bibliographic and citation databases have a well-known problem of inconsistency in the data at micro-level and meso-level, affecting the quality of bibliometric searches and the evaluation of research performance. The unification method applies parametrized finite-state graphs (P-FSG) and involves three stages: (1) breaking of corporate source data in independent units of analysis; (2) creation of binary matrices; and (3) drawing finite-state graphs. This procedure was tested on university departmental addresses, downloaded from the ISI Web of Science. Evaluation was in terms of an adaptation of the measures of precision and recall. The results demonstrate the usefulness of this approach, though it requires some human processing.

Suggested Citation

  • Carmen Galvez & Félix Moya-Anegón, 2006. "The unification of institutional addresses applying parametrized finite-state graphs (P-FSG)," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(2), pages 323-345, November.
    • Handle: RePEc:spr:scient:v:69:y:2006:i:2:d:10.1007_s11192-006-0156-3
    DOI: 10.1007/s11192-006-0156-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-006-0156-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-006-0156-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carmen Galvez & Félix Moya-Anegón, 2007. "Standardizing formats of corporate source data," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(1), pages 3-26, January.
    2. Yongwen Huang & Jiao Li & Tan Sun & Guojian Xian, 2020. "Institution information specification and correlation based on institutional PIDs and IND tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 381-396, January.
    3. Zehra Taşkın & Umut Al, 2014. "Standardization problem of author affiliations in citation indexes," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 347-368, January.
    4. Pascal Cuxac & Jean-Charles Lamirel & Valerie Bonvallot, 2013. "Efficient supervised and semi-supervised approaches for affiliations disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 47-58, October.
    5. Sjoerd Hardeman, 2013. "Organization level research in scientometrics: a plea for an explicit pragmatic approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1175-1194, March.
    6. Shuiqing Huang & Bo Yang & Sulan Yan & Ronald Rousseau, 2014. "Institution name disambiguation for research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 823-838, June.
    7. Omar Hernando Avila-Poveda, 2014. "Technical report: the trend of author compound names and its implications for authorship identity identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 833-846, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:69:y:2006:i:2:d:10.1007_s11192-006-0156-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.