[Purpose/significance] This article proposes a method of data set construction in domain analysis based on journal topic similarity, which focuses on solving the problem that data set construction cannot be realized in the cases that established subject classification cannot be gained and complete keywords be listed in some databases, and typical institutions and existing core journals in a filed cannot be chosen.[Method/process] This method combines the citation analysis, journal literatures couple analysis and mapping knowledge domains to determine the representative journal groups of a subject, and then constructs the data set to meet the different demands by different combination.[Result/conclusion] This method can meet the demand of different levels of macro, medium and micro, with simple and flexible process but a low degree of human intervention. It is proved that it can effectively solves the problem of data sets construction in some field by empirical study of a specific field, and has reference value for the related research in future.
Liu Minjuan
,
Zhang Xuefu
,
Yan Yun
,
Chen Lu
. Method and Empirical Study on Data Set Construction in Domain Analysis Based on Journal Topic Similarity[J]. Library and Information Service, 2016
, 60(10)
: 115
-122
.
DOI: 10.13266/j.issn.0252-3116.2016.10.016
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