Patent Document ID: 9031897
Application ID: 13429041

Base Claim:
1. A method for use with a first classification model that classifies an input into one of a plurality of classes, wherein the first classification model was built using labeled training data, wherein the labeled training data comprises a plurality of items of labeled training data, wherein each of the plurality of items of labeled training data is labeled with one of the plurality of classes, the method comprising acts of: obtaining unlabeled input for the first classification model; building a similarity model that represents similarities between the unlabeled input and the labeled training data; and using a programmed processor and the similarity model to evaluate the labeled training data to identify a subset of the plurality of items of labeled training data that is more similar to the unlabeled input than a remainder of the labeled training data.

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Claim 7:
7. The method of claim 1 , further comprising: using the similarity model to identify one or more items of unlabeled input that are less similar to the labeled training data than a remainder of the unlabeled input; obtaining labels for the one or more items of unlabeled input that are less similar to the labeled training data to create one or more items of labeled test input; and using the one or more items of labeled test input and at least a portion of the plurality of items of labeled training data to: retrain the first classification model; and/or build a second classification model.