1. A computer-implemented method comprising: obtaining training data including; for each of one or more original queries: (i) one or more features of the original query, (ii) one or more features of a revised query which was generated by a query revisor for the original query, and (iii) a label indicating whether the revised query is a successful revision of the original query; training, using the training data obtained for each of the one or more original queries that includes, for each respective original query, (i) the one or more features of the original query, (ii) the one or more features of the revised query which was generated by the query revisor for the original query, and (iii) the label indicating whether the revised query is a successful revision of the original query, a predictive model for predicting a likelihood that a given revised query is a successful revision of a given original query; and after receiving a particular original query, (a) using the predictive model to predict a likelihood that a particular revised query is a successful revision of the particular original query, and (b) determining whether to submit the particular revised search query to a search engine based on the likelihood.
1. A computer-implemented method comprising: obtaining training data including; for each of one or more original queries: (i) one or more features of the original query, (ii) one or more features of a revised query which was generated by a query revisor for the original query, and (iii) a label indicating whether the revised query is a successful revision of the original query; training, using the training data obtained for each of the one or more original queries that includes, for each respective original query, (i) the one or more features of the original query, (ii) the one or more features of the revised query which was generated by the query revisor for the original query, and (iii) the label indicating whether the revised query is a successful revision of the original query, a predictive model for predicting a likelihood that a given revised query is a successful revision of a given original query; and after receiving a particular original query, (a) using the predictive model to predict a likelihood that a particular revised query is a successful revision of the particular original query, and (b) determining whether to submit the particular revised search query to a search engine based on the likelihood. 10. The method of claim 1 , wherein the one or more features of the original query include a quantity of search results associated with each original query.