Implementation method of intelligent EPG recommendation engine
A technology of recommendation engine and implementation method, which is applied in the field of intelligent EPG recommendation engine implementation, and can solve the problems affecting user experience, the utilization rate of on-demand resources is less than 20%-30%, and the inability to realize automatic association and seamless switching between live broadcast and on-demand , to achieve the effect of improving the value of content operation and monetization of TV traffic, improving resource utilization and perfect experience
Inactive Publication Date: 2018-01-19
上海视畅信息科技有限公司
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Problems solved by technology
The on-demand library has a lot of content, but only a small amount of content in the first few pages is presented to users and watched, and the utilization rate of on-demand resources is less than 20%-30%
In addition, live broadcast and on-demand (including playback) are often separated, and each on-demand content provider will have its own on-demand entry, which cannot realize automatic association and seamless switching between live and on-demand
Scenario 1: The user wants to watch the content of his favorite program while watching live TV. If there are 100 channels, the user has to switch channels 100 times to find the content. The whole process greatly affects the user experience
Method used
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[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0020] Such as figure 1 Shown, a kind of intelligent EPG recommendation engine implementation method, described intelligent EPG recommendation engine implementation method comprises the following steps:
[0021] Step S1: collect the EPG program library from the whole network and generate in-depth EPG data;
[0022] In practical applications, the whole network collecting EPG program library and generating in-depth EPG data may include: collecting the EPG progr...
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The invention discloses an implementation method of an intelligent EPG recommendation engine. The method comprises the following steps: acquiring an EPG program library in a whole network and generating deep EPG data; recommending directly broadcasted hot content in real time and integrating the directly broadcasted hot content into the deep EPG data according to social data; integrating directlybroadcasted data, on-demand data, and replay data, associating and recommending the same kind of programs and fusing the same kind of programs into the deep EPG data based on unified metadata and a clustering algorithm; recommending personalized directly broadcasted, on-demand and replay program content and fusing the same into the deep EPG data based on user's viewing behavior data; subjecting the original EPG information to cross validation, information filtering, and rule matching, and matching the original EPG information with an enhanced database to generate deep EPG data to expand the EPG data. On the basis, based on the intelligent recommendation engine and a social discovery engine, live broadcast associating recommendation, live broadcast associating on demand, live broadcast current live broadcast, and personalized live broadcast recommendation are achieved.
Description
technical field [0001] The invention relates to the field of television video, in particular to a method for realizing an intelligent EPG recommendation engine. Background technique [0002] Since the beginning of live TV, TV has been with people. People enjoy high-definition viewing experience on live TV. Live TV and on-demand are the rigid needs of TV viewers. The traditional EPG (Electronic Program Guide) centers on channels, and users switch channels back and forth, but they cannot find what they want to watch. The on-demand library has a lot of content, but only a small amount of content in the first few pages is presented to users and watched, and the utilization rate of on-demand resources is less than 20%-30%. In addition, live broadcast and on-demand (including playback) are often separated, and each on-demand content provider will have its own on-demand entry, which cannot realize automatic association and seamless switching between live and on-demand. Scenario 1...
Claims
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IPC IPC(8): H04N21/258H04N21/43H04N21/432H04N21/435H04N21/462
Inventor 张超刘晚祥王守军
Owner 上海视畅信息科技有限公司