Constructing Knowledge Base for Chinese Geographical Name
Li Xiaomin,Wang Hao(),Li Yueyan,Zhao Meng
School of Information Management, Nanjing University, Nanjing 210023, China Jiangsu Key Laboratory of Data Engineering and Knowledge Service (Nanjing University),Nanjing 210093, China
[Objective] This paper uses linked data technology to study the evolution of geographical names in China, aiming to more effectively conduct digital humanity research. [Methods] First, we constructed the knowledge base CGNE_Onto for the evolution of Chinese geographical names. Then, we formulated the strong and weak marker words to identify evolution type sentences from the historical data. Third, we utilized the BERT-BiLSTM-CRF model to identify the time and place name entities from the evolution type sentences. Fourth, we used the newly generated entities as classes to build the ontology knowledge base, which was visualized from the perspective of direct and indirect path relationship. Finally, we analyzed the numbers and reasons of different evolution types in each dynasty. [Results] The proposed model intuitively demonstrated the evolution of geographical names, and provided some new directions for the analysis of geographical names data. [Limitations] The experimental data set needs to be expanded to improve the quality of evolution feature words. [Conclusions] The knowledge base for place names clearly shows their historical evolutions, as well as the evolution types in different dynasties.
李晓敏,王昊,李跃艳,赵萌. 数字人文视域下中国行政区划地名演化知识库构建及分析研究*[J]. 数据分析与知识发现, 2022, 6(11): 139-153.
Li Xiaomin,Wang Hao,Li Yueyan,Zhao Meng. Constructing Knowledge Base for Chinese Geographical Name. Data Analysis and Knowledge Discovery, 2022, 6(11): 139-153.
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