3. The method of claim 1 , wherein a classification confidence level for a given document is indicative of an accuracy of an assignment of a classification of the given document and is based on a measure of a degree to which data included in the given document matches attributes of the classification.
1. A computer-implemented method comprising: identifying, within a set of documents that have been classified within a hierarchical taxonomy using a classification algorithm, documents having a classification confidence level that is below a predetermined confidence level threshold; disassociating the identified documents from their respective classifications based on the classification level being below the predetermined confidence level threshold; obtaining, from a different classifier, a new classification within the hierarchical taxonomy for each of the identified documents; associating each of the newly classified documents with a highest classification confidence level for its respective new classification; including the newly classified documents in a trusted corpus of documents that are used to train the classification algorithm; determining a distribution of classifications of the newly classified documents within the trusted corpus of documents; updating the classification algorithm based on the trusted corpus of documents, such that the classification algorithm is configured to classify documents to promote a classification distribution that is in accordance with the determined distribution of classifications; and applying the updated classification algorithm to at least a portion of the set of documents to obtain new classifications within the taxonomy or new classification confidence levels for the portion of the set of documents, such that the at least a portion of the set of documents are classified in accordance with the classification distribution.