DID-ACTE: Digging into Data: Automating Chinese Text Extraction

The Automating Data Extraction from Chinese Texts Project aims to provide humanists and social scientists with a means of transforming 2200 years of Chinese texts into structured data. The project will develop an open-source platform (MARKUS) that allows users to apply sophisticated text-mining techniques to a wide variety of historical and literary texts. Users will be able to tag and extract personal names, dates, place names, official titles and postings, kinship ties, other social relationships, and other user-defined content. The platform will be tested against 2000 local histories spanning an 800-year period and roughly 20,000 letters and 500 notebooks dating from the seventh through the thirteenth century. Data extracted from the sample repositories will be used to enrich text-mining applications and will also be made available for research through open-access online databases and data archives.

-didacte: related to teaching; (self-)taught; learned (independently)