1. A computer-readable storage medium containing instructions for controlling a computer system to calculate relevance of a document to a user, by a method comprising: providing click-through data generated when users submitted queries to a search engine and selected a document from results provided by the search engine; identifying 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; identifying user clusters of users and query clusters of queries such that each user is in only one user cluster and each query is in only one query receiving from a user a query; searching for documents to be provided as results of the received query; for each document of the results of the received query, determining a probability that the user from whom the query was received will find the 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, the smoothing including: smoothing via backoff by: when the identified triplets include a triplet for the user, query, and document, setting a first probability based on a discounted count of the number of identified triplets for the user, query, and document and the number of triplets for the user and query; and when the identified triplets do not include a triplet for the user, query, and document, setting the first probability based on the number of identified triplets for the query and the document and the number of identified triplets for the document and based on a normalization constant; when the identified triplets include a triplet for the query and document, smoothing via clustering by setting a second probability based on a probability that a user in the user cluster that includes the user from whom the query was received selects the document from the query; and when the identified triplets do not include a triplet for the query and document, smoothing via content similarity by: identifying the query cluster to which the query is most similar; and setting the second probability based on a probability that a user selects the document from a query that is in the query cluster; and combining the first probability and the second probability into an overall probability of the document; and displaying an indication of the documents to the user from whom the query was received in an order based on the combined overall probabilities of the documents.