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Natural language processing applications in library and information science

机译:自然语言处理在图书馆和信息科学中的应用

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Purpose With the recent developments in information technologies, natural language processing (NLP) practices have made tasks in many areas easier and more practical. Nowadays, especially when big data are used in most research, NLP provides fast and easy methods for processing these data. The purpose of this paper is to identify subfields of library and information science (LIS) where NLP can be used and to provide a guide based on bibliometrics and social network analyses for researchers who intend to study this subject. Design/methodology/approach Within the scope of this study, 6,607 publications, including NLP methods published in the field of LIS, are examined and visualized by social network analysis methods. Findings After evaluating the obtained results, the subject categories of publications, frequently used keywords in these publications and the relationships between these words are revealed. Finally, the core journals and articles are classified thematically for researchers working in the field of LIS and planning to apply NLP in their research. Originality/value The results of this paper draw a general framework for LIS field and guides researchers on new techniques that may be useful in the field.
机译:目的随着信息技术的最新发展,自然语言处理(NLP)的实践使许多领域的任务变得更加容易和实用。如今,尤其是在大多数研究中使用大数据时,NLP提供了快速,简便的方法来处理这些数据。本文的目的是确定可以使用NLP的图书馆和信息科学(LIS)子领域,并为打算研究该主题的研究人员提供基于文献计量学和社会网络分析的指南。设计/方法/方法在本研究范围内,通过社交网络分析方法检查和可视化了6,607种出版物,包括在LIS领域中发表的NLP方法。结果在评估获得的结果之后,将显示出版物的主题类别,这些出版物中的常用关键字以及这些词之间的关系。最后,为在LIS领域工作并计划在研究中应用NLP的研究人员按主题对核心期刊和文章进行主题分类。原创性/价值本文的结果为LIS领域绘制了一个通用框架,并为研究人员提供了在该领域可能有用的新技术的指南。

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