信息资源管理学报 ›› 2019, Vol. 9 ›› Issue (1): 46-65.doi: 10.13365/j.jirm.2019.01.046

• 研究论文 • 上一篇    下一篇

时序分析相关方法在信息检索研究中的应用

王彦妍 张进   

  • 收稿日期:2017-10-30 出版日期:2019-01-26 发布日期:2019-01-26
  • 作者简介:王彦妍,博士,讲师,研究方向为信息检索,社交媒体和用户行为,Email:yanyanwangruc@ruc.edu.cn;张进,博士,博士生导师,教授,研究方向为信息可视化,人机交互,消费者健康信息学等。

Applications of Temporal Analysis in Information Retrieval Studies

Wang Yanyan Zhang Jin   

  • Received:2017-10-30 Online:2019-01-26 Published:2019-01-26

摘要:

时序分析是自然科学和人文社会科学研究的常用方法,在信息检索领域也被广泛使用。本文采用定性与定量相结合的研究方法回顾并分析了1991至2016年时序分析的相关方法在信息检索领域内的应用情况。本文在Web of Science,EBSCOhost和ProQuest三个数据库中检索了1991至2016年信息检索领域内使用时序分析相关方法的期刊论文、会议论文和学位论文,共计2240篇。本文采用趋势分析和文本内容分析方法对所获得的文献进行梳理和研究。研究结果显示在信息检索领域中,自2004年起时序分析方法的应用呈现明显上升趋势。时序分析方法包括定性和定量两大类,被广泛应用于传统(如文献计量、图书馆学等)、新兴(如社交媒体、商业智能等)的信息检索相关领域,及交叉学科(如健康信息等)的研究中。信息可视化方法和技术经常采用时序分析的理论和方法,同时也频繁地被用于时序分析的研究中。本文的研究结果将有助于信息检索领域的学者们进一步了解时序分析方法及其应用,并在日后的研究中更好地使用和创新时序分析方法。

关键词: 时序分析, 时序分析应用, 研究方法, 方法论, 信息检索

Abstract:

Nowadays in the information retrieval field, the changing world evokes the needs of exploring patterns and evolutions of certain objects, as well as predicting their future trends. This phenomenon brings increasing applications of temporal analysis, a means for exploring changes overtime. This study is a survey that examines and investigates the studies applying temporal analysis methods in the information retrieval field.
  Three databases were selected for retrieving the information retrieval studies applying temporal analysis methods. Various materials were obtained, such as research papers, proceedings, theses, and so on. Trend analysis, natural language processing approach, and manually content analysis were used for data analysis.
  The findings show that the use of temporal analysis keeps increasing rapidly from 2004. Both qualitative and quantitative analysis methods have been applied for temporal analysis. Information visualization technologies are also frequently employed in these studies. Temporal analysis strengthens the information retrieval studies in traditional and emerging information-retrieval-related areas and relevant cross field research areas.
  These findings help researchers gain insights into temporal analysis and its applications in information retrieval, which will assist them to use these methods and create new temporal analysis methods for various research topics in their future studies.

Key words: Temporal analysis, Temporal analysis application, Research methods, Methodology, Information retrieval

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