5. A method comprising: acquiring at one or more servers, each of the servers having a processor and a memory, a plurality of eigenvectors, each having a corresponding eigenvalue, wherein the plurality of eigenvectors are based on a plurality of tokenized electronic documents having unstructured text, the plurality of tokenized electronic documents forming a data matrix, and the unstructured text includes background terms and nonbackground terms; and classifying the plurality of eigenvectors and their corresponding eigenvalues into one or more background eigenvectors and background eigenvalues, and one or more nonbackground eigenvectors and nonbackground eigenvalues, wherein the background eigenvectors correspond to the background terms and the nonbackground eigenvectors correspond to nonbackground terms; acquiring a threshold; comparing the nonbackground eigenvalues with the threshold; and providing the nonbackground eigenvectors whose corresponding nonbackground eigenvalues exceed the threshold, wherein the provided nonbackground eigenvectors are used for clustering the plurality of documents.
5. A method comprising: acquiring at one or more servers, each of the servers having a processor and a memory, a plurality of eigenvectors, each having a corresponding eigenvalue, wherein the plurality of eigenvectors are based on a plurality of tokenized electronic documents having unstructured text, the plurality of tokenized electronic documents forming a data matrix, and the unstructured text includes background terms and nonbackground terms; and classifying the plurality of eigenvectors and their corresponding eigenvalues into one or more background eigenvectors and background eigenvalues, and one or more nonbackground eigenvectors and nonbackground eigenvalues, wherein the background eigenvectors correspond to the background terms and the nonbackground eigenvectors correspond to nonbackground terms; acquiring a threshold; comparing the nonbackground eigenvalues with the threshold; and providing the nonbackground eigenvectors whose corresponding nonbackground eigenvalues exceed the threshold, wherein the provided nonbackground eigenvectors are used for clustering the plurality of documents. 6. The method of claim 5 , wherein the threshold is set by a user, by a human operator other than a user, or from a data storage.