摘要
科技领域情报分析中,文献集构造有多种方式,但目前尚不清楚这些方式间的差别及可靠性。推动科技情报分析方法科学化的第一步,是探索能保证分析结果可靠性的领域文献集构造方法。因此,本文旨在通过实证分析量化地解答这一问题。以“人工智能”领域为例,本文在充分考虑科技情报分析多种任务场景(包括不同分析元素、不同元素数量、排序与否等)的前提下,设计了3个递进式的实验,分别为:①当前几种主流文献集构造方式间,所得结果差异性如何?②这些文献集构造方式所得结果的可靠性如何?③对这些文献集进行组合是否能提高最终分析结果的可靠性?实验结果表明,粗粒度元素(如国家)情报分析任务上,现有文献集构造方式结果差异不大,可靠性较高;但在细粒度元素(特别是作者)情报分析任务上,现有文献集构造方式结果差异明显,可靠性较低。不同情报分析任务上可以相应地挑选最合适的文献集构造方式。对现有文献集构造方式所得文献集进行组合,可靠性提升并不明显。总之,优化文献集构造方式是当前科技情报分析中必须重点关注的问题。最后,基于量化指标,本文给出了科技情报分析中在文献集构造层面上提高可靠性的一些建议,以及未来研究的一些思路。
In scientific and technical intelligence analysis,there are several methods in which documents can be collected;however,differences between these methods and their reliabilities are not well-understood.A manner in which scientific intelligence analysis can be promoted is to explore methods to collect field documents that can guarantee the reliability of analysis results.Therefore,this study aims to address this question quantitatively via an empirical analysis.First,the field of artificial intelligence is considered as an example along with the various task scenarios of scientific and technical intelligence analysis(including different analysis elements,element numbers,and sorting methods).Three progressive experiments are then designed in this study,each addressing one of the following:(1)the differences among the mainstream methods used to collect documents;(2)the reliability of these methods;and(3)the reliability of the final analysis results when the different methods are combined.The experimental results demonstrate that there is a slight difference and high re‐liability between these collection methods in intelligence analysis tasks of coarse-grained elements such as countries.However,when the intelligence analysis tasks can implemented by different researchers,the results of the existing collected methods are evidently different and their reliability is low.In different intelligence analysis tasks,we can select a relatively suitable manner to collect documents.The improvement in the reliability is not evident when the documents are collected by combining different methods.In other words,optimizing the collection of documents is crucial for the analysis of scientific and technical intelligence.Finally,based on quantitative indicators,this paper presents method to improve the reliability of scientific and technical intelligence analysis in terms of collecting documents along with future scope.
作者
陈果
邵雨
王曰芬
Chen Guo;Shao Yu;Wang Yuefen(Department of Information Management,Nanjing University of Science and Technology,Nanjing 210094;Jiangsu Science and Technology Collaborative Innovation Center of Social Public Safety,Nanjing 210094)
出处
《情报学报》
CSSCI
CSCD
北大核心
2020年第10期1034-1045,共12页
Journal of the China Society for Scientific and Technical Information
基金
国家社会科学基金重大项目“面向知识创新服务的数据科学理论与方法研究”(16ZDA224)。
关键词
领域知识分析
科技情报分析
文献计量
文献集构造
数据质量
domain knowledge analysis
scientific intelligence analysis
bibliometrics
document collections construction
data quality
