期刊
INFORMATION PROCESSING & MANAGEMENT
卷 41, 期 6, 页码 1548-1572出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ipm.2005.03.021
关键词
automatic indexing; full text analysis; text-based clustering; mapping of science; bibliometrics
In the present study results of an earlier pilot study by Glenisson, Glanzel and Persson are extended on the basis of larger sets of papers. Full text analysis and traditional bibliometric methods are serially combined to improve the efficiency of the two individual methods. The text mining methodology already introduced in the pilot study is applied to the complete publication year 2003 of the journal Scientometrics. Altogether 85 documents that can be considered research articles or notes have been selected for this exercise. The outcomes confirm the main results of the pilot study, namely, that such hybrid methodology can be applied to both research evaluation and information retrieval. Nevertheless, Scientometrics documents published in 2003 cover a much broader and more heterogeneous spectrum of bibliometrics and related research than those analysed in the pilot study. A modified subject classification based on the scheme used in an earlier study by Schoepflin and Glanzel has been applied for validation purposes. (c) 2005 Elsevier Ltd. All rights reserved.
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