Data processing method and apparatus, computer device, and storage medium

A computer device, comprising:

• one or more processors;
• and
• one or more memories, the one or more memories storing therein at least one computer program, and the at least one computer program being loaded and executed by the one or more processors and causing the computer device to perform operations including:
• determining position information for a plurality of texts and a plurality of pictures of an article:
• constructing a relative position encoding matrix based on the position information, wherein the relative position encoding matrix includes a plurality of elements, and each element of the plurality of elements represents a respective relative position information between a text, of the plurality of texts of the article, corresponding to a column to which the respective element belongs and a picture, of the plurality of pictures of the article, corresponding to a row to which the respective element belongs;
• determining relative position features between the plurality of texts and the plurality of pictures based on the relative position encoding matrix, the relative position features characterizing sequences and distances between textual data corresponding to the plurality of texts of the article and picture data corresponding to the plurality of pictures of the article, wherein the relative position features include a textual feature and a picture feature of the article;
• extracting a textual semantic feature of the textual data, and fusing the textual semantic feature and a textual position feature of the textual data to obtain the textual feature characterizing the textual data in the article;
• extracting a picture depth feature of the picture data, and fusing the picture depth feature and a picture position feature to obtain the picture feature characterizing picture data in the article;
• determining a first interaction feature for the textual feature based on a partial feature associated with the textual feature in the picture feature, wherein the first interaction feature characterizes the textual feature fused with the picture feature;
• determining a second interaction feature for the picture feature based on a partial feature associated with the picture feature in the textual feature, wherein the second interaction feature characterizes the picture feature fused with the textual feature;
• obtaining a cross-modal interaction feature by fusing the first interaction feature and the second interaction feature;
• and
• determining an article classification to which the article belongs based on the cross-modal interaction feature.

A non-transitory computer-readable storage medium, storing therein at least one computer program, the at least one computer program being loaded and executed by a processor of a computer device and causing the computer device to perform operations including:

• determining position information for a plurality of texts and a plurality of pictures of an article;
• constructing a relative position encoding matrix based on the position information, wherein the relative position encoding matrix includes a plurality of elements, and each element of the plurality of elements represents a respective relative position information between a text, of the plurality of texts of the article, corresponding to a column to which the respective element belongs and a picture, of the plurality of pictures of the article, corresponding to a row to which the respective element belongs;
• determining relative position features between the plurality of texts and the plurality of pictures based on the relative position encoding matrix, the relative position features characterizing sequences and distances between textual data corresponding to the plurality of texts of the article and picture data corresponding to the plurality of pictures of the article, wherein the relative position features include a textual feature and a picture feature of the article;
• extracting a textual semantic feature of the textual data, and fusing the textual semantic feature and a textual position feature of the textual data to obtain the textual feature characterizing textual data in the article;
• extracting a picture depth feature of the picture data, and fusing the picture depth feature and a picture position feature to obtain the picture feature characterizing picture data in the article;
• determining a first interaction feature for the textual feature based on a partial feature associated with the textual feature in the picture feature, wherein the first interaction feature characterizes the textual feature fused with the picture feature;
• determining a second interaction feature for the picture feature based on a partial feature associated with the picture feature in the textual feature, wherein the second interaction feature characterizes the picture feature fused with the textual feature;
• obtaining a cross-modal interaction feature by fusing the first interaction feature and the second interaction feature;
• and
• determining an article classification to which the article belongs based on the cross-modal interaction feature.