Automatic Methods for Coding Historical Occupation Descriptions to Standard Classifications

Kirby, G., Carson, J., Dunlop, F., Dibben, C., Dearle, A., Williamson, L., Garrett, E., Reid, A. (2015) 3 43-60 Springer International Publishing ISBN: 978-3-319-19883-5

Other information: Abstract

The increasing availability of digitised registration records presents a significant opportunity for research in many fields including those of human geography, genealogy and medicine. Re-examining original records allows researchers to study factors such as occupation, cause of death, illness and geographic region. This can be facilitated by coding these factors to standard classification. This chapter describes work to develop a method for automatically coding the occupations of 29 million Scottish birth, death and marriage records, containing around 50 million occupation descriptions, to standard classifications. A range of approaches using text processing and supervised machine learning is evaluated, achieving classification performance of 75% micro-precision/recall, 61% macro-precision and 66% macro-recall on a smaller test set. Further development that may be needed for classification of the full data set is discussed.

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