基于TF-IDF和N-gram的语言学关键词变异研究

Q4 Computer Science

Journal of Computing and Information Technology Pub Date : 2023-09-28 DOI:10.20532/cit.2022.1005566

Yuyao Li, Xueyi Wen, Xingyu Liu

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引用次数: 0

摘要

自然语言处理(NLP)的快速发展为弥合语言之间的鸿沟带来了巨大的希望。它的主要创新应用之一是使用广泛的数据来探索一个主题的历史趋势。然而，由于索绪尔是现代语言学的先驱，在语言学研究中对该领域的变化进行的研究工作相对不足，无法全面揭示语言学的发展趋势。为了追踪语言学研究热点的变化，我们使用了来自Web of Science的3万多篇语言学相关文献及其标题的数据集，并将NLP技术应用于由关键词和出版年份组成的数据。研究发现，关键词与NGRAM的共现关系及其与年份的关系可以有效地反映语言学研究主题的变化。本研究可望为语言学及相关学科提供进一步的见解和新方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Research on Keywords Variations in Linguistics Based on TF-IDF and N-gram

The rapid development of natural language processing (NLP) holds great promise for bridging the divide among languages. One of its main innovative applications is to use broad data to explore the historical trend of a subject. However, since Saussure pioneered modern linguistics, there is relatively inadequate research work done in the linguistic research on the field's variations to comprehensively reveal the linguistic trends. To trace the changes in linguistic research hotspots, we use a dataset of more than 30,000 linguistics-related literature with their titles from the Web of Science and apply NLP techniques to the data consisting of their keywords and publication years. It is found that the co-occurrence relationship between keywords, NGRAM, and their relationship with years can effectively present changes in linguistic research themes. This research is supposed to provide further insights and new methods that can be applied in the field of linguistics and related disciplines.

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来源期刊

Journal of Computing and Information Technology Computer Science-Computer Science (all)

CiteScore

0.60

自引率

0.00%

发文量

审稿时长

26 weeks

期刊介绍： CIT. Journal of Computing and Information Technology is an international peer-reviewed journal covering the area of computing and information technology, i.e. computer science, computer engineering, software engineering, information systems, and information technology. CIT endeavors to publish stimulating accounts of original scientific work, primarily including research papers on both theoretical and practical issues, as well as case studies describing the application and critical evaluation of theory. Surveys and state-of-the-art reports will be considered only exceptionally; proposals for such submissions should be sent to the Editorial Board for scrutiny. Specific areas of interest comprise, but are not restricted to, the following topics: theory of computing, design and analysis of algorithms, numerical and symbolic computing, scientific computing, artificial intelligence, image processing, pattern recognition, computer vision, embedded and real-time systems, operating systems, computer networking, Web technologies, distributed systems, human-computer interaction, technology enhanced learning, multimedia, database systems, data mining, machine learning, knowledge engineering, soft computing systems and network security, computational statistics, computational linguistics, and natural language processing. Special attention is paid to educational, social, legal and managerial aspects of computing and information technology. In this respect CIT fosters the exchange of ideas, experience and knowledge between regions with different technological and cultural background, and in particular developed and developing ones.