Abstract: The present specification discloses a model training method and apparatus, a service processing method and apparatus, a storage medium, and a device.

Abstract: Implementations of the present specification provide a data processing method, apparatus, and device. The method includes: obtaining to-be-detected target data, and obtaining a target probability that the target data corresponds to each candidate user intention, where the target data includes input data of a user in a human-computer interaction process; dividing the target data to obtain a plurality of pieces of subdata, and obtaining, based on a predetermined gradient integration algorithm, a contribution of each piece of subdata to a correspondence between the target data and each candidate user intention; and determining a target user intention corresponding to the target data based on the target probability that the target data corresponds to each candidate user intention and the contribution of each piece of subdata to the correspondence between the target data and each candidate user intention.

Abstract: Intent recognition is described. Obtained data to be recognized is preprocessed to obtain target data. Feature extraction processing is performed on the target data based on an intent recognition model to obtain a linear feature and a non-linear feature of the target data, where the intent recognition model is obtained by optimizing and training a bidirectional encoder representations from transformers (BERT) model. Intent recognition processing is performed based on the linear feature, the non-linear feature, and the intent recognition model to obtain an intent recognition result of the obtained data to be recognized.