Abstract: The present disclosure provides an intelligent cataloging method for all-media news based on multi-modal information fusion understanding, which obtains multi-modal fusion features by unified representation and fusion understanding of video information, voice information, subtitle bar information, and character information in the all-media news, and realizes automatic slicing, automatic cataloging description, and automatic scene classification of news using the multi-modal fusion features. The beneficial effect of the present disclosure is that it realizes the complete process of automatic comprehensive cataloging for the all-media news, and improves the accuracy and generalization of the cataloging method, and greatly reduces the manual cataloging time by generating stripping marks, news cataloging descriptions, news classification labels, news keywords, and news characters based on the fusion of multi-modes of video, audio, and text.

Abstract: Disclosed is a text data attribution description and generation method based on text character features, comprising: obtaining text data to be processed, decomposing the text data to obtain a plurality of characters, and performing a feature space representation on the text data based on the characters; storing the features of the text data through a horizontal position of the characters and an association between different characters according to the feature space representation of the text data; generating a text data attribution according to feature storage results of the text data.