| 摘要 |
After a categorization process has been run, the scores of the top-two ranking categories along with the size or number of features in the object being categorized, are passed to a confidence assignment process. This determines a value for the confidence in the top category based on the evidence afforded by the input parameters. The magnitude of this confidence value will determine whether the system can accept the automatic categorization results, or whether human involvement is required. This invention also describes the process of determining the optimal value of an internal scaling parameter in the confidence assignment process. The construction of a threshold table based on this parameter is also described. The threshold table matches confidence values against error levels. For a given error rate the previously assigned confidence determines whether the categorization results can be accepted without need for human intervention. This invention maximizes the number of objects that can be automatically processed, for a given error rate.
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