10. A computer-implemented method for providing visual suggestions for cluster classification, comprising: obtaining one or more clusters comprising uncoded documents from a set, each cluster associated with a visual representation; designating a different set of reference documents that are each classified with a code, each code associated with a visual representation different from the representations of the clusters and from the representations of the remaining classification codes; identifying a cluster center in one of the clusters and comparing the cluster center to one or more of the reference documents; identifying those of the reference documents that are similar to the cluster based on the comparison; and providing a visual suggestion for assigning one of the classification codes to the cluster comprising the cluster center, comprising displaying the visual representation of the cluster comprising the cluster center together with a list of all of the reference documents similar to the cluster and the visual representations of the classification codes of each of the similar reference documents in the list.
10. A computer-implemented method for providing visual suggestions for cluster classification, comprising: obtaining one or more clusters comprising uncoded documents from a set, each cluster associated with a visual representation; designating a different set of reference documents that are each classified with a code, each code associated with a visual representation different from the representations of the clusters and from the representations of the remaining classification codes; identifying a cluster center in one of the clusters and comparing the cluster center to one or more of the reference documents; identifying those of the reference documents that are similar to the cluster based on the comparison; and providing a visual suggestion for assigning one of the classification codes to the cluster comprising the cluster center, comprising displaying the visual representation of the cluster comprising the cluster center together with a list of all of the reference documents similar to the cluster and the visual representations of the classification codes of each of the similar reference documents in the list. 12. A method according to claim 10 , further comprising: determining a similarity between the clusters and organizing the clusters along one or more spines based on the similarity, each of the spines comprising a vector; identifying cluster centers for all of the clusters along one of the spines and generating a score vector for the spine based on the cluster centers; generating score vectors for the reference documents based on content of the reference documents; comparing the score vector for the spine to the score vectors for the reference documents and identifying those of the reference documents that are similar to the spine based on the comparison of the spine score vector to the score vectors of the reference documents; visually representing the classification codes of each of the reference documents similar to the spine as a suggestion for assigning one of the classification codes to the spine.