11. A system for identifying reference documents for use in classifying uncoded documents, comprising: a database to store a set of reference documents that are each classified with a code; a clustering module to designate a set of clusters each comprising uncoded documents from a different set than the reference documents; a similarity module to select at least one uncoded document from the set, to compare the at least one uncoded document with each of the reference documents, and to identify one or more reference documents that satisfy a threshold of similarity with the at least one uncoded document; a processing module to process the classification codes associated with the similar reference documents, comprising: a type module to determine a number of different types of the classification codes associated with the similar reference documents; a presence module to determine one or more of a presence and absence of the similar reference documents with each type of the different classification codes; and a quantity module to determine for each type of the classification codes a quantity of the similar reference documents; a suggestion module to display a visual classification suggestion based on at least one of the presence and the absence and the quantity and the number of the types via a display of the at least one of the uncoded document and the similar reference documents; a classification module receiving a classification code of one of the types for the at least one uncoded document from a human reviewer based on the suggestion; and a processor to execute the modules.
11. A system for identifying reference documents for use in classifying uncoded documents, comprising: a database to store a set of reference documents that are each classified with a code; a clustering module to designate a set of clusters each comprising uncoded documents from a different set than the reference documents; a similarity module to select at least one uncoded document from the set, to compare the at least one uncoded document with each of the reference documents, and to identify one or more reference documents that satisfy a threshold of similarity with the at least one uncoded document; a processing module to process the classification codes associated with the similar reference documents, comprising: a type module to determine a number of different types of the classification codes associated with the similar reference documents; a presence module to determine one or more of a presence and absence of the similar reference documents with each type of the different classification codes; and a quantity module to determine for each type of the classification codes a quantity of the similar reference documents; a suggestion module to display a visual classification suggestion based on at least one of the presence and the absence and the quantity and the number of the types via a display of the at least one of the uncoded document and the similar reference documents; a classification module receiving a classification code of one of the types for the at least one uncoded document from a human reviewer based on the suggestion; and a processor to execute the modules. 14. A system according to claim 11 , wherein the similarity module comprises: a score module to form a score vector for each uncoded document and each reference document; and a vector similarity module to calculate a similarity metric between the score vectors for the uncoded documents and reference documents.