Streaming media content distribution method and system

Abstract

The present invention relates to a method and system for distributing streaming media content, comprising the following steps: when a user orders, a server receives the user's order request, and the server pushes a plurality of qualified streaming media contents in a streaming media library to a cache module according to the order request , and according to the on-demand request, a plurality of streaming media contents that are pushed to the cache module are set up in the cache module to create a recommendation table, and at the same time, the server authenticates the user identity. After the identity verification is passed, the cache module pushes the recommendation table to the client, According to the user's selection of the content of the recommendation table at the user end, it is directly linked to the cache module to obtain the streaming media content; when the streaming media content is distributed to the user end for display, the recommendation table rolls up to form a floating point, and when the streaming media content is displayed, The floating point is rolled up again; when the close option on the floating point is clicked, the floating point closes and sends a clear command to the cache module at the same time, and the cache module receives the clear command to clear the streaming media content corresponding to the recommendation table.

Description

technical field [0001] The invention relates to the field of network technology, in particular to a streaming media content distribution method and system. Background technique [0002] With the development of new media and self-media, there are more and more existing media data streams. In particular, when on-demand on the Internet, there are a lot of streaming media content, and the server generally recommends them according to hot streams (streaming media content with a large amount of on-demand) To the client, or to recommend on-demand content to the user based on the user's historical on-demand habits, and when the user searches for on-demand, it also recommends the corresponding content to the client. After the user clicks to browse, the user end forms a large number of caches. If there is no manual clearing at the client end, it will accumulate more and more, resulting in a large memory storage at the client end, and when a large number of client ends perform on-deman...

AI Technical Summary

Problems solved by technology

[0002] With the development of new media and self-media, there are more and more existing media data streams. In particular, when on-demand on the Internet, there are a lot of streaming media content, and the server generally recommends them according to hot streams (streaming media content with a large amount of on-demand) To the client, or to recommend on-demand content to the user based on the user's historical on-demand habits, and when the user searches for on-demand, it also recommends the corresponding content to the client. After the user clicks to browse, the user end forms a large number of caches. If there is no manual clearing at the client end, it will accumulate more and more, resulting in a large memory storage at the client end, and when a large number of client ends perform on-demand broadcasts, when the streaming media content is directly extracted from the storage area, the server will also be paralyzed or run. slow

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