Abstract: A computer-implemented system and method for analyzing clusters of coded documents is provided. Clusters of documents are displayed and at least a portion of the documents are each associated with a classification code. A representation of each document is provided based on the associated classification code or an absence of the associated classification code. A search query with search terms is received. Each search term is associated with one of the classification codes. Those documents that satisfy the search query are identified and the representations of the identified documents are changed based on the classification codes associated with the search terms. The change in representation provides an indication of agreement between the classification code of such document and the classification codes of the search terms, or an indication of disagreement between the classification code of the document and the classification codes of the search terms.

Abstract: A computer-implemented system and method for analyzing clusters of coded documents is provided. Clusters of documents are displayed and at least a portion of the documents are each associated with a classification code. A representation of each document is provided based on the associated classification code or an absence of the associated classification code. A search query with search terms is received. Each search term is associated with one of the classification codes. Those documents that satisfy the search query are identified and the representations of the identified documents are changed based on the classification codes associated with the search terms. The change in representation provides an indication of agreement between the classification code of such document and the classification codes of the search terms, or an indication of disagreement between the classification code of the document and the classification codes of the search terms.

Abstract: A computer-implemented system and method for generating document training sets is provided. Unclassified documents are provided to two or more classifiers. A classification code assigned to each unclassified document is received. A determination is made as to whether a disagreement exists between classification codes assigned to a common unclassified document via different classifiers. The common unclassified document with a disagreement in classification codes are provided for further review. Results of the further review include one of a new classification code and confirmation of one of the assigned classification codes. The unclassified documents for which a disagreement exists are grouped as a training set.