Abstract
This paper compares entity resolution results obtained by using both probabilistic and deterministic matching when applied to the deduplication of student enrollment data. The approach outlined in this paper uses deterministic matching to represent equivalence for the calculation of weights to be used in probabilistic matching based on the Fellegi-Sunter model.
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