Abstract: A model-based data processing method and apparatus that can extract a first training sample set to obtain a second training sample set and a query video, the first training sample set including different types of video samples; process the second training sample set through an embedded layer network in an action recognition model to obtain a first frame feature sequence; process the query video through the embedded layer network to obtain a second frame feature sequence; process the first frame feature sequence through a time sequence relation network in the action recognition model to obtain a first time sequence relation descriptor; process the second frame feature sequence through the time sequence relation network to obtain a second time sequence relation descriptor; and adjust a model parameter of the action recognition model according to the first time sequence relation descriptor and the second time sequence relation descriptor.