@inproceedings{1a98a38767094e80bbe933e8e1f5f693,
title = "Automatic cleaning and linking of historical census data using household information",
abstract = "Historical census data captures information about our ancestors. These data contain the social status at a certain point time. They contain valuable information for genealogists, historians, and social scientists. Historical census data can be used to reconstruct important aspects of a particular era in order to trace the changes in households and families. Record linkage across different historical census datasets can help to improve the quality of the data, enrich existing census data with additional information, and facilitate improved retrieval of information. In this paper, we introduce a domain driven approach to automatically clean and link historical census data using recent developments in group linkage techniques. The key contribution of our approach is to first detect households, and to use this information to refine the cleaned data and improve the accuracy of linking records between census datasets. We have developed a two-step linking approach which first links individual records using approximate string similarity measures, and then performs a group linking based on the previously detected households. The results show that this approach is effective and can greatly reduce the manual efforts required for data cleaning and linking by social scientists.",
keywords = "Data cleaning, Domain knowledge, Group linking, Historical census data, Record linkage",
author = "Zhichun Fu and Peter Christen and Mac Boot",
year = "2011",
doi = "10.1109/ICDMW.2011.35",
language = "English",
isbn = "9780769544090",
series = "Proceedings - IEEE International Conference on Data Mining, ICDM",
pages = "413--420",
booktitle = "Proceedings - 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011",
note = "11th IEEE International Conference on Data Mining Workshops, ICDMW 2011 ; Conference date: 11-12-2011 Through 11-12-2011",
}