1. In a computerized search system in which queries are submitted by users who receive, in response, a list of documents selected from a corpus of documents wherein the list comprises documents deemed responsive to a user's query, a method of determining relevance of the documents comprising: obtaining, at a server computer comprising a processor, the query from a user; determining initial probabilities that at least one leaf category of a taxonomy contains documents relevant to the query, at least one of the initial probabilities being non-zero, wherein the at least one leaf category contains indexed documents predetermined to be related to one another and the initial probabilities are numeric values between zero and one; determining a relevance of the documents matching the query in each leaf category having non-zero initial probability; and determining a relevance of documents to the query based on the initial probabilities of the at least one leaf category and the relevance of the documents matching the query, wherein determining the relevance of documents to the query comprises: for each particular leaf category containing a particular document, determining a weighted relevance value by multiplying a determined relevance of the particular document matching the query by the initial probability that the particular leaf category includes relevant documents; generating updated probabilities that the nodes of the taxonomy contain relevant documents by weighting each of the relevance of documents to the query, wherein weights used to generate the updated probabilities decay monotonically with the probability that a document matching the query resides in the particular node; determining an updated relevance of documents to the query based on the updated probabilities and the probability that a document matching the query resides in the particular node; and summing the weighted relevance values to determine the relevance of the particular document to the query.
10. The method of claim 1 , further comprising repeatedly generating the updated probabilities of the nodes based on the previous updated probabilities of the nodes and re-determining the updated relevance of documents to the query.