Abstract: The method and apparatus for categorizing an item based on Record Linkage Theory is disclosed. A related method and apparatus for assigning a confidence level to the categorization process is disclosed. In one aspect, the item to be categorized is parsed into at least one token. At least one category that contains the token in the training set is identified. A weight is calculated for each token with respect to a first category. Weights are combined to determine the total weight of the first category. The weighting process is repeated for each relevant category. Where one of a plurality of threshold values is met or exceeded, the item may be automatically assigned to the category with the highest total weight. The combination of threshold values may be selected based on the confidence level associated with that combination of threshold values. Weights for each relevant category, possibly ordered, may be presented.

Abstract: The method and apparatus for categorizing an item based on Record Linkage Theory is disclosed. A related method and apparatus for assigning a confidence level to the categorization process is disclosed. In one aspect, the item to be categorized is parsed into at least one token. At least one category that contains the token in the training set is identified. A weight is calculated for each token with respect to a first category. Weights are combined to determine the total weight of the first category. The weighting process is repeated for each relevant category. Where one of a plurality of threshold values is met or exceeded, the item may be automatically assigned to the category with the highest total weight. The combination of threshold values may be selected based on the confidence level associated with that combination of threshold values. Weights for each relevant category, possibly ordered, may be presented.