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A scaling approach to record linkage

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DLAW02 - Data linkage: techniques, challenges and applications

Co-authors: Mario Cortina-Borja (UCL), Katie Harron (LSHTM)

With increasing availability of large data sets derived from administrative and other sources, there is an increasing demand for the successful linking of these to provide rich sources of data for further analysis. The very large size of such datasets and the variation in the quality of the identifiers used to carry out linkage means that existing approaches based upon ‘probabilistic’ models can make heavy computational demands. They are also based upon questionable assumptions. In this paper we suggest a new approach, based upon a scaling algorithm, that is computationally fast, requires only moderate amounts of storage and has intuitive appeal. A comparison with existing methods is given. 

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