10. One or more computer storage media having a system embodied thereon including computer-executable instructions that, when executed, perform a method for identifying query rewriting replacement terms, the system comprising: an intake component that receives a list of related string pairs, each pair comprising a first string and a second string, wherein the first string of each related string pair is a user search query extracted from user click log data, the user click log data including one or more search query sessions including at least one dwell time associated with one or more search results and a number of links clicked; a statistical machine translation model that, for one or more of the related string pairs: receives the string pair as inputs, identifies one or more pairs of corresponding terms, each pair of corresponding terms including a first term from the first string and a second term from the second string, and calculates a probability of relatedness for each of the one or more pairs of corresponding terms; a characterization component that, upon determining that the probability of relatedness of a pair of corresponding terms calculated by the statistical machine translation model exceeds a threshold, characterizes the second term as a query term replacement for the first term; and a candidate term population component that, for each pair of corresponding terms for which the calculated probability of relatedness exceeds a threshold, incorporates the first term, the second term, and the probability of relatedness for the pair into a query rewriting candidate database.
10. One or more computer storage media having a system embodied thereon including computer-executable instructions that, when executed, perform a method for identifying query rewriting replacement terms, the system comprising: an intake component that receives a list of related string pairs, each pair comprising a first string and a second string, wherein the first string of each related string pair is a user search query extracted from user click log data, the user click log data including one or more search query sessions including at least one dwell time associated with one or more search results and a number of links clicked; a statistical machine translation model that, for one or more of the related string pairs: receives the string pair as inputs, identifies one or more pairs of corresponding terms, each pair of corresponding terms including a first term from the first string and a second term from the second string, and calculates a probability of relatedness for each of the one or more pairs of corresponding terms; a characterization component that, upon determining that the probability of relatedness of a pair of corresponding terms calculated by the statistical machine translation model exceeds a threshold, characterizes the second term as a query term replacement for the first term; and a candidate term population component that, for each pair of corresponding terms for which the calculated probability of relatedness exceeds a threshold, incorporates the first term, the second term, and the probability of relatedness for the pair into a query rewriting candidate database. 11. The media of claim 10 , wherein an expectation/maximization algorithm is used to train the statistical machine translation model.