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arXiv · 1504.02148

Mining and discovering biographical information in Difangzhi with a language-model-based approach

Peter K. Bol·Chao-Lin Liu·Hongsu Wang
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Abstract

We present results of expanding the contents of the China Biographical Database by text mining historical local gazetteers, difangzhi. The goal of the database is to see how people are connected together, through kinship, social connections, and the places and offices in which they served. The gazetteers are the single most important collection of names and offices covering the Song through Qing periods. Although we begin with local officials we shall eventually include lists of local examination candidates, people from the locality who served in government, and notable local figures with biographies. The more data we collect the more connections emerge. The value of doing systematic text mining work is that we can identify relevant connections that are either directly informative or can become useful without deep historical research. Academia Sinica is developing a name database for officials in the central governments of the Ming and Qing dynasties.

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Peter K. Bol, Chao-Lin Liu, Hongsu Wang. 2015-04-08. Mining and discovering biographical information in Difangzhi with a language-model-based approach. https://arxiv.org/abs/1504.02148

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