19. A method for clustering reference documents to generate suggestions for classification of uncoded documents, comprising the steps of: designating a set of reference documents each associated with one of a plurality of classification codes and a visual representation of that classification code comprising at least one of a shape and a symbol, wherein the visual representation of each of the classification codes is different from the visual representations of the remaining classification codes; obtaining a set of uncoded documents each associated with a visual representation different from the visual representations of the classification codes; selecting one or more of the coded reference documents and combining the one or more coded reference documents selected with the uncoded documents as a set of combined documents; grouping the combined set of documents into clusters, comprising: determining a similarity between each document; and grouping the documents into the clusters based on the similarity; identifying at least one cluster of the clusters with the coded reference documents; and visually depicting relationships between the uncoded documents and the one or more coded reference documents in the at least one cluster as suggestions for classifying the uncoded documents in that cluster, comprising displaying the visual representation associated with each of the coded reference documents in that cluster and the visual representation associated with each of the uncoded documents in that cluster, wherein the steps are performed by a suitably programmed computer.
19. A method for clustering reference documents to generate suggestions for classification of uncoded documents, comprising the steps of: designating a set of reference documents each associated with one of a plurality of classification codes and a visual representation of that classification code comprising at least one of a shape and a symbol, wherein the visual representation of each of the classification codes is different from the visual representations of the remaining classification codes; obtaining a set of uncoded documents each associated with a visual representation different from the visual representations of the classification codes; selecting one or more of the coded reference documents and combining the one or more coded reference documents selected with the uncoded documents as a set of combined documents; grouping the combined set of documents into clusters, comprising: determining a similarity between each document; and grouping the documents into the clusters based on the similarity; identifying at least one cluster of the clusters with the coded reference documents; and visually depicting relationships between the uncoded documents and the one or more coded reference documents in the at least one cluster as suggestions for classifying the uncoded documents in that cluster, comprising displaying the visual representation associated with each of the coded reference documents in that cluster and the visual representation associated with each of the uncoded documents in that cluster, wherein the steps are performed by a suitably programmed computer. 21. A method according to claim 19 , wherein the one or more coded reference documents are selected from at least one of a predefined, customized, or arbitrary reference document set.