1. A method in a computer system with a processor and memory for identifying clusters of documents, the method comprising: providing sentences having words, each sentence representing a topic of a document; for each sentence representing the topic of a document, identifying a generalized sentence for the sentence, the generalized sentence representing a generalization of words of the sentence, a generalization including a part of speech of a word; identifying by the processor generalized sentence patterns for the identified generalized sentences, each generalized sentence pattern representing a pattern of generalizations of the generalized sentences; grouping the identified generalized sentence patterns into groups of generalized sentence patterns based on similarity of the generalized sentence patterns; selecting identified generalized sentence patterns to guide the identification of clusters wherein the groups of generalized sentence patterns are used to guide the identification of clusters; and applying a cluster identification algorithm to identify clusters of documents using the selected generalized sentence patterns to guide the identification such that documents whose generalized sentences are similar to the same generalized sentence pattern are identified as being in the same cluster wherein similarity of generalized sentence patterns is defined as: sim ⁡ ( p , q ) = { 1 , p ⋐ q ⋀ sup ⁡ ( q ) sup ⁡ ( p ) ≥ min_conf 0 , otherwise ( 3 ) where sim(p,q) represents the similarity of generalized sentence pattern p to generalized sentence pattern q, min conf represents a minimum confidence needed to establish similarity, and sup(p) represents support of generalized sentence p to be a generalized sentence pattern defined as: 
 sup( p )=|{ s|s∈S p ⊂ s}| where s is a generalized sentence in the set of sentences S.