Abstract: Techniques for a classification system with methodology for enhanced verification are described. In one approach, a classification computer trains a classifier based on a set of training documents. After training is complete, the classification computer iterates over a collection unlabeled documents uses the trained classifier to predict a label for each unlabeled document. A verification computer retrieves one of the documents assigned a label by the classification computer. The verification computer then generates a user interface that displays select information from the document and provides an option to verify the label predicted by the classification computer or provide an alternative label. The document and the verified label are then fed back into the set of training documents and are used to retrain the classifier to improve subsequent classifications. In addition, the document is indexed by a query computer based on the verified label and made available for search and display.

Abstract: Techniques for a classification system with methodology for enhanced verification are described. In one approach, a classification computer trains a classifier based on a set of training documents. After training is complete, the classification computer iterates over a collection unlabeled documents uses the trained classifier to predict a label for each unlabeled document. A verification computer retrieves one of the documents assigned a label by the classification computer. The verification computer then generates a user interface that displays select information from the document and provides an option to verify the label predicted by the classification computer or provide an alternative label. The document and the verified label are then fed back into the set of training documents and are used to retrain the classifier to improve subsequent classifications. In addition, the document is indexed by a query computer based on the verified label and made available for search and display.