Pushing method and device of media contents, storage medium and electronic device

Abstract

The invention discloses a pushing method and device of media contents, a storage medium and an electronic device. The method includes: receiving a pushing request, wherein the pushing request is usedfor requesting pushing of the media contents to a target object; in response to the pushing request, selecting the to-be-pushed first media contents from candidate media contents through a target model, wherein the target model is used for selecting the first media contents, of which attributes match the target object, from the candidate media contents according to association relationships learned at a first moment, the first media contents are different from second media contents, of which attributes match the target object, selected from the candidate media contents by the target model according to association relationships learned at a second moment, and the second moment is different from the first moment; and pushing the first media contents to the target object. The method solves the technical problem of lower accuracy of media contents recommended for users in the related art.

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 a recommendation system to recommend streaming media mes...

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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