Media content pushing method and device, storage medium and electronic device

Abstract

The invention discloses a media content pushing method and device, a storage medium and an electronic device. The media content pushing method comprises the steps: acquiring a push request of a firstterminal, wherein the push request is used for requesting to push media content to the first terminal; obtaining a first log of the first terminal, a second log of the second terminal and a relation vector between the second terminal and the first terminal, wherein media content browsed by the first account on the first terminal is recorded in the first log, and media content browsed by the secondaccount on the second terminal is recorded in the second log, and the relation vector is used for representing the relation between applications installed on the first terminal and the second terminal; selecting target media content from the media content library based on the first log, the second log and the relationship vector; and in response to the push request, pushing the target media content to the first terminal. According to the media content pushing method and device, the technical problem of relatively low accuracy of media content recommended to the user in the related art is solved.

Description

technical field [0001] The present invention relates to the Internet field, in particular, to a method and device for pushing media content, a storage medium, and an electronic device. Background technique [0002] With the rapid development of Internet technology, the number of services on the network has also increased dramatically. However, this growth far exceeds the scope that individuals or systems can accept, process and effectively utilize. In this environment, in order to solve the "information overload" problem brought about by the growth of the number of services, a service recommendation system that can meet the needs of different users emerged as the times require. The service recommendation theory and related technologies have become a hot topic in academia and industry. popular research topics. [0003] In order to improve user experience and increase data hits of media content, related technologies use recommendation systems to recommend streaming media mess...

AI Technical Summary

Problems solved by technology

The above-mentioned content-based streaming media message recommendation method will lead to a lower richness of streaming media messages pushed to users, a narrower recommendation area, no surprises in the recommendation, and easy to fall into popular recommendations. Since the attributes are fixed and unchanged, the recommended content Accuracy is not guaranteed, thereby degrading user experience

[0004] For the above problems, no effective solution has been proposed

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