11. A method for clustering similar documents, comprising the steps of: identifying concepts for a set of documents; determining occurrence frequencies of each concept in the document set; calculating an inner product quantifying a similarity for each of the documents in the set with one or more clusters of documents based on the occurrence frequencies of the concepts; mapping each document to each of the document clusters based on the inner product; identifying those documents with the smallest inner products as most relevant to a theme; and generating a matrix as a representation of the document and cluster mappings, wherein the steps are executed by a suitably-programmed computer.
14. A method according to claim 11 , further comprising: determining those concepts that are most relevant; and summarizing the most relevant concepts in a matrix that maps the concepts to clusters of documents.