13. A computer system for calculating relevance of a document, comprising: a click-through data store providing click-through data generated when users submitted queries to a search engine and selected a document from results provided by the search engine; a memory containing computer-executable instructions of a component that identifies user, query, and document triplets from the click-through data, each triplet indicating that the user of the triplet submitted the query of the triplet and the user selected the document of the triplet from results of the query provided by the search engine; a component that receives an input user, an input query, and input documents as an input triplet; and a component that determines a probability that the input user will find each input document relevant by performing a smoothing of the identified triplets to account for sparseness of the triplets and calculating the probability based on the smoothed triplets, wherein the determined probability is based at least in part on identified triplets identified for users other than the input user and wherein the probability is the probability of an input document given the input user and the input query when the corresponding user, query, and document triplet is identified and is the probability of the input document given the input query otherwise and wherein a back-off factor is applied to the probability; and a processor for executing the computer-executable instructions stored in the memory.
13. A computer system for calculating relevance of a document, comprising: a click-through data store providing click-through data generated when users submitted queries to a search engine and selected a document from results provided by the search engine; a memory containing computer-executable instructions of a component that identifies user, query, and document triplets from the click-through data, each triplet indicating that the user of the triplet submitted the query of the triplet and the user selected the document of the triplet from results of the query provided by the search engine; a component that receives an input user, an input query, and input documents as an input triplet; and a component that determines a probability that the input user will find each input document relevant by performing a smoothing of the identified triplets to account for sparseness of the triplets and calculating the probability based on the smoothed triplets, wherein the determined probability is based at least in part on identified triplets identified for users other than the input user and wherein the probability is the probability of an input document given the input user and the input query when the corresponding user, query, and document triplet is identified and is the probability of the input document given the input query otherwise and wherein a back-off factor is applied to the probability; and a processor for executing the computer-executable instructions stored in the memory. 16. The computer system of claim 13 wherein the probability is based on similarity between an input document and document clusters identified based on relationships between users and queries.