10. In a computing environment, a system comprising: a computer; a topic identification mechanism implemented at least in part by the computer and configured for extracting topics from a set of web pages that correspond to a query, wherein the topics are noun phrases that represent subjects of the web pages; a topic match mechanism implemented at least in part by the computer and coupled to the topic identification mechanism and configured for computing a relevance score for each extracted topic, wherein each relevance score is based on a predicted match level from a group of match levels comprising a first match level that indicates an exact match between the each extracted topic and the query, a second match level that indicates a same meaning between the each extracted topic and the query, a third match level that indicates that the each extracted topic is relevant to the query, a fourth match level that indicates that the each extracted topic is irrelevant to the query, and a fifth match level that indicates that the each extracted topic does not match the query, and wherein the predicted match level is based on a conditional probability model P(L|Q→T) where L denotes a level, and where Q→T denotes an event that comprises generating topic T from query Q; and a page ordering mechanism implemented at least in part by the computer and coupled to the topic match mechanism and configured for ranking the web pages relative to one another based on the relevance score computed for each web page.
11. The system of claim 10 wherein the topic identification mechanism is further configured for extracting topics from at least one of a group comprising a title of the web page, anchor text of the web page, a uniform resource locator (“URL”) referencing the web page, tags assigned to the web page, a query associated with the web page, and a body of the web page.