10. The computer program product of claim 9 , wherein the selection of one or more documents from the plurality of documents is received in response to monitoring what documents referenced in the initial search results are accessed by the user and prompting the user to indicate whether each accessed document is relevant to what the user is searching for.
9. A computer program product, the computer program product comprising a computer usable storage medium having computer usable program code for processing search results, the code being configured for: receiving a search request against a corpus of documents, wherein the search request specifies one or more search terms; generating an initial set of search results, wherein the initial set of search results identifies a plurality of documents responsive to the search request, ranked in an initial ordering, and wherein each of the plurality of documents contains text; receiving user indication of: (i) at least one document relevant to the one or more search terms and (ii) at least one document irrelevant to the one or more search terms; by operation of one or more computer processors when executing the computer usable program code, training a new statistical classifier using each relevant document as a positive training example to form a first category of documents recognized by the statistical classifier and using each irrelevant document as a negative training example to form a second category of documents recognized by the statistical classifier, wherein the at least one relevant document and the at least one irrelevant document form a training set for the new statistical classifier; supplying each document in the initial set of search results and not in the training set, to the trained statistical classifier to obtain a measure of similarity between the respective document and at least one of the categories recognized by the trained statistical classifier; supplying one or more documents from the corpus and not included in the set of initial search results, to the trained statistical classifier to obtain a measure of similarity between each of the one or more documents and at least one of the categories recognized by the trained statistical classifier; re-ranking the initial set of search results based on the measures of similarity obtained from the trained statistical classifier, comprising ranking each document having a measure of similarity to the first category of documents that exceeds a first user-configurable threshold, ahead of each document having a measure of similarity to the second category of documents that exceeds a second user-configurable threshold; and outputting the re-ranked search results for display to a user.