1. A method for displaying relationships between concepts to provide classification suggestions via inclusion, comprising the steps of: designating reference concepts each associated with a classification code and a visual representation of that classification code comprising at least one of a shape, a color, and a symbol, wherein each concept comprises nouns and noun phrases with common semantic meaning that are extracted from a set of documents; extracting uncoded concepts from unclassified documents and associating each of the uncoded concepts with a visual representation different from the representations of the classification codes; forming a grouped concept set by grouping a subset of the classified reference concepts with a set of uncoded concepts; generating clusters, each comprising a portion of the uncoded concepts and the classified reference concepts of the grouped concept set, comprising: determining a similarity between the concepts in the grouped concept set; and putting the concepts whose similarity exceeds a threshold into one of the clusters: visually depicting relationships between the uncoded concepts and one or more classified reference concepts in at least one of the clusters as suggestions for classifying the uncoded concepts in that cluster, comprising displaying the visual representation associated with each of the classified reference concepts in that cluster and the visual representation of each of the uncoded concepts in that cluster, wherein the steps are performed by a suitably programmed computer.