3. The method of claim 1 , wherein said producing of the user-specific query-dependent topic distribution Pr(T u |q,θ u ) comprises: receiving a user-independent language model; receiving a user-specific query-independent distribution Pr(T u |θ u ) describing a probability that the particular user u is intent on finding identified topics; and computing the user-specific query-dependent topic distribution Pr(T u |q,θ u ) based on the user-independent language model and the user-specific query-independent distribution Pr(T u |θ u ), using Bayes' rule.
1. A method comprising: receiving a query q from a particular user u who intends to find results that satisfy the query q with respect to a topic T u , the particular user u being characterized by user information θ u ; producing a generic topic distribution Pr r (T|q) associated with the query q that is germane to a population of generic users; producing a user-specific query-dependent topic distribution Pr(T u |q,θ u ) associated with the query q for the particular user u; generating personalized results for the particular user u based on the generic topic distribution Pr r (T|q) and the user-specific query-dependent topic distribution Pr(T u |q,θ u ); and forwarding the personalized results to the particular user u.