IDEAS home Printed from https://ideas.repec.org/a/igg/jswis0/v9y2013i4p41-70.html
   My bibliography  Save this article

Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia

Author

Listed:
  • Philipp Singer

    (Knowledge Technologies Institute, Graz Technical University, Graz, Austria)

  • Thomas Niebler

    (Data Mining and Information Retrieval Group, University of Würzburg, Würzburg, Germany)

  • Markus Strohmaier

    (Computer Science Institute, University of Koblenz-Landau, Koblenz, Germany, & Computational Social Science Group, GESIS, Cologne, Germany)

  • Andreas Hotho

    (Data Mining and Information Retrieval Group, University of Würzburg, Würzburg, Germany)

Abstract

In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.

Suggested Citation

  • Philipp Singer & Thomas Niebler & Markus Strohmaier & Andreas Hotho, 2013. "Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 9(4), pages 41-70, October.
    • Handle: RePEc:igg:jswis0:v:9:y:2013:i:4:p:41-70
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijswis.2013100103
    Download Restriction: no
    ---><---

    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:igg:jswis0:v:9:y:2013:i:4:p:41-70. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.