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Document-document similarity approaches and science mapping: experimental comparison of five approaches
Stockholm University, University Library.
2009 (English)In: Journal of Informetrics, ISSN 1751-1577, E-ISSN 1875-5879, 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
2009. Vol. 3, no 1, 49-63 p.
Keyword [en]
Citation data, Textual data, Data source combination, Cluster analysis, Science mapping
National Category
Other Social Sciences not elsewhere specified
Identifiers
URN: urn:nbn:se:su:diva-26004DOI: 10.1016/j.joi.2008.11.003ISI: 000262496700005OAI: oai:DiVA.org:su-26004DiVA: diva2:201783
Available from: 2009-03-05 Created: 2009-03-05 Last updated: 2017-12-13

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