International Business Machines Corporation

Norman S Adams

Scott Schumacher

Scott Ellard

Embodiments of the invention provide a system and method of automatically generating weights for matching data records. Each field of a record may be compared by an exact match and/or close matches and each comparison can result in a mathematical score which is the sum of the field comparisons. To sum up the field scores accurately, the automatic weight generation process comprises an iterative process. In one embodiment, initial weights are computed based upon unmatched-set probabilities and default discrepancy weights associated with attributes in the comparison algorithm. A bulk cross-match is performed across the records using the initial weights and a candidate matched set is computed for updating the discrepancy probabilities. New weights are computed based upon the unmatched probabilities and the updated discrepancy probabilities. Test for convergence between the new weights and the old weights. Repeat with the new weight table until the weights converge to their final value.

System and method for automatic weight generation for probabilistic matching

Embodiments of systems and methods for comparing attributes of a data record are presented herein. In some embodiments, a weight is based on a comparison of the name (or other) attributes of data records. In some embodiments, an information score may be calculated for each of two name attributes to be compared to get an average information score for the two name attributes. The two name attributes may then be compared against one another to generate a weight between the two attributes. This weight can then be normalized to generate a final weight between the two business name attributes. Comparing attributes according to embodiments disclosed herein can facilitate linking data records even if they comprise attributes in languages which do not use the Latin alphabet.

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Cave Creek, AZ, United States of America

Norman S Adams