| 马宇驰,牟冬梅,杨鑫禹.优化关键词利用策略的共词分析研究[J].数字图书馆论坛,2021,(12):34~40 |
| 优化关键词利用策略的共词分析研究 |
| Research on Co-word Analysis Based on Keyword Optimization |
| 投稿时间：2021-12-01 |
| DOI：10.3772/j.issn.1673-2286.2021.12.006 |
| 中文关键词: 共词分析；关键词；关键词组；主动健康；优化方案；DDA |
| 英文关键词: Co-word Analysis; Keywords; Keyword Groups; Proactive Health; Optimization Plan; DDA |
| 基金项目:本研究得到国家自然科学基金项目“信息链视域下电子病历数据驱动健康服务供给侧决策的路径与模式研究”（编号：71974074）资助。 |
| 作者 | 单位 | | 马宇驰 | 吉林财经大学图书馆 | | 牟冬梅 | 吉林大学第一医院 | | 杨鑫禹 | 吉林大学公共卫生学院 |
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| 摘要点击次数: 1735 |
| 全文下载次数: 1226 |
| 中文摘要: |
| 本文提出关键词利用策略的优化方案，解决小数量级概念失焦、关键词组概念缺失等问题，优化共词分析结果，以发现潜在研究热点，拓展研究热点主题识别的深度。关键词利用策略优化方案在高频词共词分析的基础上，引入关键词与关键词组相结合的处理方案，通过调整数据集范围，实现共词分析结果优化。实证部分以“主动健康”主题为例，使用DDA软件，完成基于关键词利用策略优化方案的共词分析，探测主动健康的学科主题热点。在初始发现的5类研究领域、12个热点之外，基于关键词利用策略优化方案的共词分析扩展识别了7个潜在热点话题，补充发现5个复合词组表达的研究概念。关键词利用策略优化方案令小数量级概念聚焦形成类团，在聚类过程中得到表达，令关键词组代表的概念得到完整呈现。 |
| 英文摘要: |
| This paper propose a keyword optimization plan to solve the problems of small-scale concept defocus and keyword group concept missing, optimize the results of co-word analysis, and expand the breadth and depth of research hotspots recognition. The keyword optimization mode is based on the high-frequency word co-word analysis, introduces the processing method of combining keywords and keyword groups, and obtains the optimization of the co-word analysis results by adjusting the range of the data set. The empirical part takes the topic of “proactive health” as an example, uses DDA software to complete a co-word analysis based on the keyword optimization plan, and detects the research hotspots of proactive health. A keyword optimization plan is proposed, which optimizes the co-word analysis by adjusting the scope of the data set and introducing keyword group recognition. In the empirical research part, in addition to the 5 types of research fields and 12 hotspots initially discovered, the co-word analysis based on the keyword optimization plan expanded to identify 7 potential hotspots and supplemented the discovery of 5 research concepts expressed by compound phrases. The keyword optimization mode enables small-scale concepts to focus on forming clusters, which can be expressed in the clustering process, and also enables the concepts represented by keyword groups to be fully presented. |
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