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运用模糊集理论扩展达万的期刊选择模型:对生物医学信息学期刊进行排名

Use of fuzzy set theory to extend Dhawan's journal selection model: ranking the biomedical informatics serials.

作者信息

Sittig D F

机构信息

Clinical Systems Research and Development, Partners Healthcare System, Chestnut Hill, MA 02167, USA.

出版信息

Bull Med Libr Assoc. 1999 Jan;87(1):43-9.

Abstract

OBJECTIVE

Experts disagree on the parameters to use to identify the "best" serials within a scientific field. The author set out to develop an extension to Dhawan's journal selection model for ranking serials in any scientific field.

METHODS

Comparison of three different instantiations of Dhawan's model were used to rank thirty-four biomedical informatics serials.

RESULTS

The first instantiation of Dhawan's model identified seven serials and divided them into two groups. The second instantiation of Dhawan's model identified twelve serials and separated them into two groups. Using fuzzy set theory the new extended model produced a rank ordered list of the top twelve biomedical informatics serials.

CONCLUSIONS

Use of fuzzy set theory to assign set membership and combine data in Dhawan's journal selection model allows one to: (1) eliminate the need to determine arbitrary cutoff points for inclusion of serials within each of Dhawan's evaluation criteria categories, (2) combine data from disparate sources, and (3) obtain a rank-ordered list of the biomedical informatics serials rather than simply identifying a set of the "top" serials. Such a ranked list provides librarians and researchers alike with the information necessary to help them make their biomedical informatics serial selection decisions based on objective, quantifiable data.

摘要

目的

专家们对于在某一科学领域内用以确定“最佳”连续出版物的参数存在分歧。作者着手对达万的期刊选择模型进行扩展,以便对任何科学领域的连续出版物进行排名。

方法

运用达万模型的三种不同实例对34种生物医学信息学连续出版物进行排名。

结果

达万模型的第一个实例识别出7种连续出版物并将它们分成两组。达万模型的第二个实例识别出12种连续出版物并将它们分成两组。运用模糊集理论,新的扩展模型生成了生物医学信息学领域排名前12的连续出版物的有序列表。

结论

在达万的期刊选择模型中运用模糊集理论来分配集合成员资格并整合数据,能够使人们:(1)无需为达万的每个评估标准类别中连续出版物的纳入确定任意的截止点;(2)整合来自不同来源的数据;(3)获得生物医学信息学连续出版物的有序列表,而不仅仅是识别出一组“顶级”连续出版物。这样一个排名列表为图书馆员和研究人员提供了必要的信息,帮助他们基于客观、可量化的数据做出生物医学信息学连续出版物的选择决策。

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