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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