Keyword Analysis Visualization for Chinese Historical Texts

Jihui Zeng, B. Zhan, Shao Zhang, Jiajun Bie, Sheng Xiao
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引用次数: 1

Abstract

Historical texts form the basis of the study of antiquities. In the case of Chinese historical texts different genres exist, e.g. chronological and biographical works etc. The contents of these texts normally consist of complex and interrelated information which covers long time period. Traditional history research relies heavily on information extraction and analysis by human researchers. With the recent development of the internet, data science and visualization technologies, digital history gradually attracts more and more attentions and in turn significantly impacts the field of historical study through altering the accessibility of the source materials, the narrative strategy and the analytical methodologies. This paper provides a system that enhances the Chinese historical research using word segmentation, texts analysis and visualization technologies. We can improve the workflow of traditional historical research via automatically detecting important keywords in Chinese historical texts and extracting, analyzing and visualizing the relations between a keyword and other words. This does not only accelerate the text based historical study but also to a great extent increase the scope of the search and analysis of the keywords in Chinese historical texts which used to be limited by the capacity of human researchers.
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中文历史文本关键词分析可视化
历史文献是古物研究的基础。就中国的历史文本而言,存在不同的体裁,如编年体和传记作品等。这些文本的内容通常由复杂而相互关联的信息组成,涵盖了很长一段时间。传统的历史研究在很大程度上依赖于人类研究人员的信息提取和分析。随着近年来互联网、数据科学和可视化技术的发展,数字历史逐渐受到越来越多的关注,并通过改变史料的可及性、叙事策略和分析方法,对历史研究领域产生了重大影响。本文提出了一个利用分词、文本分析和可视化技术加强中国历史研究的系统。通过自动检测中文历史文本中的重要关键词,提取、分析和可视化关键词与其他关键词之间的关系,可以改善传统历史研究的工作流程。这不仅加快了基于文本的历史研究,而且在很大程度上扩大了过去受限于人类研究能力的中文历史文本关键词搜索和分析的范围。
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