24. A computer-implemented method, comprising: determining, for a current user session and by one or more computers, a user context that is indicative of a category of user interest for the user session, the determination being based on content provided to a particular user during the current user session, wherein determining the user context comprises: identifying a plurality of web pages as part of one or more contexts, each of the web pages being identified based upon inclusion of the web pages in one or more of a plurality of click models associated with the one or more contexts; determining that the content provided to the particular user during the current user session includes a particular web page from the plurality of web pages, the particular web page being identified as part of both a first context and a second context, the first context being different from the second context; obtaining a first metric for the first context, the first metric being calculated based on a frequency with which previous user sessions that included requests for the particular web page were determined to be part of the first context; obtaining a second metric for the second context, the second metric being calculated based on a frequency with which the previous user sessions that included requests for the particular web page were determined to be part of the second context; and determining that the user context is one of the first context or second context based on the first metric and the second metric; and receiving, during the user session and after determining the user context, a user search query from the particular user; and providing, by one or more computers and in response to receiving the user search query, ranked search results for the user search query, the ranking being based at least in part on a first contextual click model for the user context.
24. A computer-implemented method, comprising: determining, for a current user session and by one or more computers, a user context that is indicative of a category of user interest for the user session, the determination being based on content provided to a particular user during the current user session, wherein determining the user context comprises: identifying a plurality of web pages as part of one or more contexts, each of the web pages being identified based upon inclusion of the web pages in one or more of a plurality of click models associated with the one or more contexts; determining that the content provided to the particular user during the current user session includes a particular web page from the plurality of web pages, the particular web page being identified as part of both a first context and a second context, the first context being different from the second context; obtaining a first metric for the first context, the first metric being calculated based on a frequency with which previous user sessions that included requests for the particular web page were determined to be part of the first context; obtaining a second metric for the second context, the second metric being calculated based on a frequency with which the previous user sessions that included requests for the particular web page were determined to be part of the second context; and determining that the user context is one of the first context or second context based on the first metric and the second metric; and receiving, during the user session and after determining the user context, a user search query from the particular user; and providing, by one or more computers and in response to receiving the user search query, ranked search results for the user search query, the ranking being based at least in part on a first contextual click model for the user context. 26. The method of claim 24 , wherein each user session is defined by a login and logout time associated with a corresponding user.