| Overview |
Expanding on work accomplished through an earlier research, "Development of Historical Text Information Extraction Techniques for Compiling the Historical Events Recorded in Ming and Qing Dynasties," this project aims to build an extended information extraction system for Chinese historical documents, promoting the engagement of methodologies, approaches, and tools between information technology and humanities in support of digital humanities research. Employing natural language processing technologies, not only can the system automatically recognize keywords such as person names and place names from an extensive corpus of historical texts in an efficient manner and systematically present their temporal and spatial characteristics to establish a historical event extraction method to assist in the development of humanities-related research topics.
In view of the complexity involved in military events, it is necessary to explore the diachronic causal context and spatial variation from the content recorded in historical texts. Therefore, this project will focus on the analysis of military events in the Ming and Qing dynasties, improve the data preprocess methods, and enhance the efficacy of the Named Entity Recognition algorithm. Further, harnessing deep learning techniques, we will explore the technology of event extraction for text semantic reasoning, event detection, and recognition of complex event composition patterns. The above work will be based on the official history and expert research data, and also verify the practicality of the analysis model of this research. The method developed in this research is expected to accommodate different historical texts. It will be capable of effectively extracting historical events, assisting in analyzing the cause and effect of historical events, and further strengthening the integrated application of temporal and spatial information and historical knowledge. Moreover, it is designed to improve the effectiveness of historical events presented on the map and expand the research scope of the textual time-space integration information system in digital humanities. |
