Abstract: The embodiment of the present application discloses a method and a device for generating a ranking model. A specific embodiment of the method includes: acquiring a sample set, executing following training steps: for the samples in the sample set, inputting the query information, the first position document and the second position document in the sample into an initial model, respectively obtaining scores of the input documents, and determining a target value of the sample based on the obtained scores, a clicked bias of a first position and an unclicked bias of a second position, updating the initial model based on the target value of each sample; determining whether the initial model is completely trained; and in response to determining that the initial model is completely trained, determining the updated initial model as the ranking model.

Abstract: The embodiment of the present application discloses a method and a device for generating a ranking model. A specific embodiment of the method includes: acquiring a sample set, executing following training steps: for the samples in the sample set, inputting the query information, the first position document and the second position document in the sample into an initial model, respectively obtaining scores of the input documents, and determining a target value of the sample based on the obtained scores, a clicked bias of a first position and an unclicked bias of a second position, updating the initial model based on the target value of each sample; determining whether the initial model is completely trained; and in response to determining that the initial model is completely trained, determining the updated initial model as the ranking model.