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Document-document similarity approaches and science mapping: Experimental comparison of five approaches
Department of e-Resources, University Library, Stockholm University.
Jönköping University, The University Library.
2009 (English)In: Journal of Informetrics, ISSN 1751-1577, Vol. 3, no 1, 49-63 p.Article in journal (Refereed) Published
Abstract [en]

This paper treats document-document similarity approaches in the context of science mapping. Five approaches, involving nine methods, are compared experimentally. We compare text-based approaches, the citation-based bibliographic coupling approach, and approaches that combine text-based approaches and bibliographic coupling. Forty-three articles, published in the journal Information Retrieval, are used as test documents. We investigate how well the approaches agree with a ground truth subject classification of the test documents, when the complete linkage method is used, and under two types of similarities, first-order and second-order. The results show that it is possible to achieve a very good approximation of the classification by means of automatic grouping of articles. One text-only method and one combination method, under second-order similarities in both cases, give rise to cluster solutions that to a large extent agree with the classification.

Place, publisher, year, edition, pages
Netherlands: Elsevier BV , 2009. Vol. 3, no 1, 49-63 p.
Keyword [en]
Bibliometrics, Citation data, Text mining, Cluster analysis, Data source combination, Science mapping
Identifiers
URN: urn:nbn:se:hj:diva-7832DOI: 10.1016/j.joi.2008.11.003OAI: oai:DiVA.org:hj-7832DiVA: diva2:160369
Available from: 2009-02-13 Created: 2009-02-13 Last updated: 2009-04-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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