Abstract: This application discloses a data processing method and apparatus, a computer device, and a non-transitory computer-readable storage medium in the technical field of computers. This application, for textual data and picture data of an article, extracts a textual feature and a picture feature, respectively, and predicts an article classification to which the article belongs using a cross-modal interaction feature between the textual feature and picture feature. At the same time, this application considers the contribution degree of each of a textual modality and a picture modality to the article classification, rather than determining from a textual perspective only. In addition, the extracted cross-modal interaction feature is not a simple concatenation of the textual feature and the picture feature, which can reflect richer and deeper inter-modal interaction information, and greatly improve the identification accuracy of the article classification.

Abstract: A multimedia resource classification model training method includes acquiring an attribute information set and a training label set of training multimedia resources. The method further includes inputting the attribute information set into a multimedia resource classification model that includes a plurality of feature sub-networks and a plurality of task sub-networks. The multimedia resource classification model is configured to classify quality of multimedia resources. The method further includes vectorizing the attribute information to obtain attribute feature vectors and inputting the obtained attribute feature vectors into the plurality of task sub-networks to obtain prediction labels corresponding to the plurality tasks.