1. A computerized method of analyzing a plurality of documents, comprising: collecting and filtering terms from a plurality of documents; identifying a term-frequency vector for each of the documents; identifying a term-frequency matrix using the term-frequency vector, wherein rows of the term-frequency matrix comprise values for the term-frequency vectors; projecting the term-frequency matrix onto a lower dimensional space using latent semantic analysis, to create a transformed term matrix; developing a correlation matrix comprising columns and rows corresponding to terms of the transformed term matrix, and a plurality of elements each having a correlation value indicating a statistical relationship exclusively between two of the terms; converting the correlation values to distance values; creating a concept graph of connected components using the distance values that are greater than or less than a concept threshold, where each connected component is a concept set of terms that corresponds to a concept; and clustering documents that contain the terms of the concept set together.