Abstract: A computer-implemented method for training a query ranking machine-learning model to provide an answer for a user query in a search engine. The method obtains a first training set and training a query-ranking machine-learning mode and a query generation machine-learning model on the first training set. From a knowledge database, the query generation machine-learning model generates a second training set. The query-ranking machine-learning model filters the second training set and the query-ranking machine-learning model is retrained on the filtered training set. The steps of generating a second training set, filtering the second training set and retraining the query ranking machine-learning model on the filtered training set may be repeated several times.