Content item recommendation method and device, server and storage medium
A recommendation method and technology for content items, applied in the field of data processing, can solve problems such as poor recommendation effect of content items
Pending Publication Date: 2020-04-14
深圳市雅阅科技有限公司
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Problems solved by technology
[0005]
The embodiment of the present disclosure provides a content item recommendation method, device, server and storage medium, which can solve the problem of poor content item recommendation effect in related technologies
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[0042] In order to make the purpose, technical solution and advantages of the present disclosure clearer, the implementation manners of the present disclosure will be further described in detail below in conjunction with the accompanying drawings.
[0043] Artificial intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the nature of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, reasoning and deci...
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The invention provides a content item recommendation method and device, a server and a storage medium, which belong to the field of data processing. The method comprises the steps of obtaining a userfeature vector of a target user and content item feature vectors of a plurality of content items; inputting the user feature vector of the target user and the content item feature vectors of the plurality of content items into a content item recommendation model, and predicting the probability that the target user performs each interaction behavior on each content item by the content item recommendation model; and based on the probability of each interaction behavior, recommending a target content item in the plurality of content items to the target user, the target content item being a content item meeting a recommendation condition. According to the invention, the server can more comprehensively judge whether the user is interested in the target content item or not by predicting the probabilities of multiple interaction behaviors, and the content item meeting the user preference is recommended to the user.
Description
technical field [0001] The present disclosure relates to the field of data processing, and in particular to a content item recommendation method, device, server and storage medium. Background technique [0002] With the rapid development of network technology today, people will learn or relax through various content items on smart devices, and how to recommend content items that users are interested in to users has also attracted the attention of more and more content item recommendation platforms. [0003] In related technologies, in order to recommend content items of interest to users, the content item recommendation platform often predicts the probability of a user clicking a certain content item based on a click-through rate estimation model, and recommends the content item with the highest user click probability to the user. [0004] When using the above content item recommendation method to recommend content items, users may click on the recommended content item, but ...
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Login to View More IPC IPC(8): G06F16/9535G06N3/04G06N3/08
CPCG06F16/9535G06N3/08G06N3/045
Inventor 刘剑王亚龙刘克俊陈凯夏锋
Owner 深圳市雅阅科技有限公司