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dc.contributor.advisorBongo, Lars Ailo
dc.contributor.advisorSommerseth, Hilde Leikny
dc.contributor.authorPark, Narae
dc.date.accessioned2023-01-27T06:32:39Z
dc.date.available2023-01-27T06:32:39Z
dc.date.issued2022-08-02en
dc.description.abstractThe Historical Population Register (HPR) is a project to build the longitudinal life history of individuals by integrating the historical records of the people in Norway since the 19th century. This study attempted to improve the linking rate between the 1875-1900 censuses in HPR, which is currently low, using machine learning approaches. To this end, I developed a machine learning model for linking that is suitable for the Norwegian census and tested various algorithms, feature sets, and match selection options. I compared the results in terms of performance and match size, and also examined their representativeness to the entire population. The study results showed that the linking rate of HPR can be significantly improved by machine learning approaches while maintaining high accuracy. In addition, this study presented a reference for future use by demonstrating how the performance varies depending on the feature set and match selection. On the other hand, this study also revealed that linked data generally do not represent the population of the census, and the characteristics and degree of bias vary depending on the linking algorithm, suggesting that caution is needed when using linked data for research.en_US
dc.descriptionFor errata and source code: <a href=https://github.com/uit-hdl/rhd-linking>https://github.com/uit-hdl/rhd-linking</a>.
dc.identifier.urihttps://hdl.handle.net/10037/28399
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universitetno
dc.publisherUiT The Arctic University of Norwayen
dc.rights.holderCopyright 2022 The Author(s)
dc.subject.courseIDINF-3990
dc.subjectHistorical record linkageen_US
dc.subjectNorwegian censusen_US
dc.subjectHistorical Population registeren_US
dc.subjectMachine learningen_US
dc.titleRecord linkage of Norwegian historical census data using machine learningen_US
dc.typeMastergradsoppgaveno
dc.typeMaster thesisen


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