12. The system of claim 1 , wherein the subset of documents is based at least in part upon information received from a user.
1. A keyphrase extraction system, comprising: a processor; a term identifier that employs a noun phrase detector to identify candidate terms in a subset of documents; a probability computation component that calculates respective probability values of a joint probability of a candidate term and a document in the subset of documents associated with a collection of documents, a marginal probability of the candidate term, and a marginal probability of the document, related to each candidate term, the probability computation component further employing an inverse document frequency so that candidate terms that appear in substantially all documents of the subset of documents are given reduced weight by the system, wherein the subset of documents comprises at least two documents and contains less documents than the collection of documents, and further includes documents respectively associated with at least two different disparate domains, the at least two different disparate domains containing at least two of a directory domain containing word processing documents, an e-mail domain containing e-mails, and a web page domain containing web pages; a partial mutual information metric computation component that computes a respective partial mutual information metric for each candidate term as a function of a ratio of the probability value of the joint probability of the candidate term and the document to a product of the probability value of the marginal probability of the candidate term and the probability value of the marginal probability of the document, wherein a document-term matrix based at least in part on candidate terms and the subset of documents is employed to facilitate determination of the joint probability of the candidate term and the document; and a summarization component that identifies one or more summary keyphrases associated with the subset of documents based at least in part upon the respective partial mutual information metric for each candidate term, wherein a top quantity of candidate terms is identified as the summary keyphrases and the summarization component excludes a particular word from the identified summary keyphrases when a particular keyphrase in the top quantity of candidate terms and the top quantity of candidate terms both include the particular word.