Data open output method and device and computing equipment

Abstract

The invention discloses a data open output method which is executed in a computing device, an M * N first sparse matrix is stored in the computing equipment, an embedded model is trained according tothe matrix, the model is suitable for decomposing the input sparse matrix into at least three sub-matrixes, and two sub-matrixes are reconstructed into an output matrix. The method comprises the stepsof obtaining L user identifiers of to-be-output data, extracting original data of N user features corresponding to each user identifier, and generating an L * N second sparse matrix; splicing the second sparse matrix into the first sparse matrix to obtain a third sparse matrix; updating the first sparse matrix into a third sparse matrix, and retraining the embedded model by adopting the third sparse matrix to obtain a new embedded model; and learning the second sparse matrix by adopting the new embedded model to obtain a corresponding output matrix, and carrying out open output on the outputmatrix. The invention further discloses a corresponding data open output device and computing equipment.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a data open output method, device and computing equipment. Background technique [0002] With the rapid development of Internet technology and the increasing popularity of e-commerce, the number of network information resources has increased dramatically, and information providers always hope to obtain more user data in order to recommend commodity resources that they may be interested in according to user preferences. When the existing data provider outputs data to the data user (information provider), most of them directly output the original data in the form of plain text, which will lead to the leakage of user privacy. However, if the original data is processed into data such as labels for output, a lot of user information will be lost. The data user will recommend the most suitable product resources to the customer based on these data, and the recommendation effect will...

AI Technical Summary

Problems solved by technology

When the existing data provider outputs data to the data user (information provider), most of them directly output the original data in plain text, which will lead to the leakage of user privacy

However, if the original data is processed into data such as labels for output, a lot of user information will be lost. The data user will recommend the most suitable product resources to the customer based on these data, and the recommendation effect will be greatly reduced, affecting the landing of the product. Conversion rate

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