Cross-media data sharing representation method and user behavior analysis method and system

Abstract

The invention provides a cross-media data sharing representation method and a user behavior analysis method and system, and the cross-media data sharing representation method comprises the steps: obtaining cross-media data which comprises two types of media data: an image and a text; performing inter-media independent representation learning on each media type in the cross-media data by using a multi-mode deep belief network to obtain inter-media independent representation corresponding to each media type; performing intra-media independent representation learning on the cross-media data by using a stacked automatic encoder to obtain intra-media independent representation corresponding to each media type; and performing hierarchical combination on the inter-media independent representationand the intra-media independent representation corresponding to each media type to obtain cross-media data shared representation. According to the method, the shared representation is obtained by reserving the associated information of the inter-media data and learning the cross-media correlation, and the complex cross-media correlation can be captured, so that the shared representation method can be suitable for complex cross-media data scenes.

Description

technical field [0001] The invention relates to the technical field of cross-media data processing, in particular to a cross-media data sharing representation method, user behavior analysis method and system. Background technique [0002] With the rapid development of the Internet, various types of data (including images, texts, voices and videos, etc.) on the Internet explode in large quantities. People use machine learning methods such as clustering, classification and association rules to analyze these data, discover hidden information, and obtain valuable knowledge. Correlation information often exists among multiple types of data. Therefore, when analyzing multiple types of data, that is, cross-media data, it is necessary to process the cross-media data to obtain the correlation between different media data. [0003] At present, traditional cross-media processing methods mainly rely on common space learning, but most of these methods are based on linear projections, wh...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the embodiment of the present invention provides a cross-media data sharing representation method and system to overcome the inability of the cross-media data sharing representation method in the prior art to capture complex cross-media correlations by using a shallow network structure, thereby Difficult to apply to the problem of mining complex cross-media associations

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