发文趋势与引文趋势融合的学科研究主题优先级排序——以我国情报学学科主题为例

目的/意义]主题排序不仅是信息检索、信息组织研究的基础性问题,也是图书馆学科服务的重要工作,对学科领域研究主题进行有效排序能够帮助科研人员和科研管理部门有效把握学科领域的研究态势,准确定位科研方向,快速做出科研决策。方法/过程]基于趋势分析提出一种学科研究主题优先级排序算法。首先,在主题提取的基础上,根据发文趋势和引文趋势将每个研究主题按研究等级分为贫乏主题、热点主题、冷点主题、过热主题4个子类。然后,分别对各子类下的主题词进行优先级排序。结果/结论]在情报学领域的实验表明:本文提出的优先级排序算法能够全方位、细粒度、深层次地展示学科领域研究主题的发展等级,该方法可为从时间维度实现动态情报分析提供新的视角。

The Prioritization of Subject Research Topics Based on the Integration of Writing Trends and Citation Trends: Taking the Subject of Information Science in China as an Example

Purpose/significance] Topic sorting is not only the basic problem for information retrieval and information organization, but also an important work of subject service. The effective sorting of subject field research topics can help researchers and decision-making departments to grasp the research situation of the subject field effectively, locate the direction of scientific research accurately and make scientific research decisions quickly.Method/process] This paper proposes the prioritization algorithm based on the combination of topic extraction and trend analysis. Then it takes the research topics of Library and Information Science as an example to extract the research topics of the sample literature, and each research topic is divided into four sub-topics:poor theme, hot topic, cold point theme, and overheated topic. Next priority ranking is carried out in subclasses.Result/conclusion] The empirical results show that the priority ranking algorithm can display the development level of research topics in an all-round, fine-grained and deep way. This method provides a new perspective for realizing dynamic intelligence analysis from time dimension.