Personalized pushing system and method based on streaming computing
A streaming computing and streaming technology, applied in transmission systems, electrical components, etc., can solve problems such as high concurrency, personalized push failures, and problems in the recommendation process, to avoid request rates and ensure smooth progress.
Active Publication Date: 2020-02-18
ZHIZHESIHAIBEIJINGTECH CO LTD
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Problems solved by technology
Therefore, the recommendation system cannot be directly applied to personalized push. The server needs to automatically schedule and trigger calculations, and send the recommended results to users at regular intervals. This process is an offline process.
Unfortunately, when the number of users reaches more than tens of millions, the huge number of users requires the above calculation process to be completed in the shortest possible time, resulting in a high degree of concurrency of requests, which can easily lead to problems in the recommendation process and lead to personalization. push failure
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[0038] Exemplary embodiments of the present disclosure will be described below with reference to the accompanying drawings. In the interest of clarity and conciseness, not all features of an actual implementation are described in this specification. It should be understood, however, that many implementation-specific decisions can be made in developing any such actual implementation in order to achieve the developer's specific goals, and that these decisions may vary from implementation to implementation .
[0039] Here, it should be noted that, in order to avoid obscuring the present disclosure due to unnecessary details, only the device structure closely related to the solution according to the present disclosure is shown in the drawings, and the relationship with the present disclosure is omitted. Little other details.
[0040] It is to be understood that the present disclosure is not limited to only the described embodiments as described below with reference to the accomp...
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The invention relates to a personalized pushing system based on streaming computing, and the system comprises a user generation unit which is configured to be used for generating target user information; a user kafka unit which is configured to be used for storing target user information in a streaming manner; a user consumption unit which is configured to generate request information based on thetarget user information in the user kafka unit and call the recommendation unit based on the request information; a recommendation unit which is configured to generate recommendation content corresponding to the target user information; a result kafka unit configured to store the recommended content in a streaming manner; and a pushing unit configured to be used for pushing the stored recommendedcontent. The personalized pushing system at least has one of the following beneficial technical effects: according to the personalized pushing system, each module is independent to form a service, and the modules are connected through production and consumption of kafka, so that the system can effectively control the request rate to avoid breakdown of recommendation services, and smooth real-time pushing is guaranteed.
Description
technical field [0001] The present disclosure relates to the field of network information processing, and in particular, to a stream computing-based personalized push system and method. Background technique [0002] With the development of Internet technology, there are more and more applications on the terminal. As an important means of transmitting information, message push is an effective way to stimulate activity and is widely used by major app manufacturers. The pushed message can be manually specified, or it can be calculated by the service based on the user's interests. With the maturity of the recommendation system, it is more suitable to apply it to the push. The recommendation system can effectively find the focus of the user's attention, accurately locate the user's interest, push the content that the user is interested in, and improve the push effect. [0003] The recommendation system is often applied to the home page feed stream of the APP (the information flo...
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IPC IPC(8): H04L29/08
CPCH04L67/55
Inventor 张维健白志勇杨文家杨向军孙付伟
Owner ZHIZHESIHAIBEIJINGTECH CO LTD