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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Some bibliometric procedures for analyzing and evaluating research fields
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Some bibliometric procedures for analyzing and evaluating research fields

机译：用于分析和评估研究领域的一些生学计量程序

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摘要

Nowadays, measuring the quality and quantity of the scientific production is an important necessity since almost every research assessment decision depends, to a great extent, upon the scientific merits of the involved researchers. To do that, many different indicators have been proposed in the literature. Two main bibliometric procedures to explore a research field have been defined: performance analysis and science mapping. On the one hand, performance analysis aims at evaluating groups of scientific actors (countries, universities, departments, researchers) and the impact of their activity on the basis of bibliographic data. On the other hand, the extraction of knowledge from the intellectual, social or conceptual structure of a research field could be done by means of science mapping analysis based on bibliographic networks. In this paper, we introduce some of the most important techniques and software tools to analyze the impact of a research field and its scientific structures. Particularly, four bibliometric indices (h, g, hg and q_(2)), the h-classics approach to identify the classic papers of a research field and three free science mapping software tools (CitNetExplorer, SciMAT and VOSViewer) are shown.
机译：如今，测量科学生产的质量和数量是重要的必要性，因为几乎每项研究评估决策都在很大程度上取决于所涉研究人员的科学价值。为此，文献中已经提出了许多不同的指标。探索研究领域的两种主要的派对测量程序：性能分析和科学映射。一方面，绩效分析旨在评估科学行动者（国家，大学，部门，研究人员）的群体，以及在书目数据的基础上的影响。另一方面，可以通过基于书目网络的科学映射分析来完成研究领域的知识，社会或概念结构的知识的提取。在本文中，我们介绍了一些最重要的技术和软件工具，以分析研究领域的影响及其科学结构。特别是，四个识别研究领域的经典论文和三种自由科学映射软件工具（CitnetExplorer，SciMat和VosViewer）的H-Classics方法。

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