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Content recommendation method, computing device and storage medium

A computing device and content recommendation technology, applied in the Internet field, can solve problems such as poor user satisfaction, and achieve the effect of fewer algorithm parameters, improved CTR, and less calculation

Pending Publication Date: 2020-09-11
BEIJING QIERBULAITE TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] However, UCB is a deterministic selection strategy, which may result in the same resources returned to the user each time, and user satisfaction may be poor

Method used

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  • Content recommendation method, computing device and storage medium
  • Content recommendation method, computing device and storage medium
  • Content recommendation method, computing device and storage medium

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Embodiment Construction

[0032] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0033] figure 1 A schematic diagram of a content recommendation system 100 according to an embodiment of the present invention is shown. Such as figure 1 As shown, the content recommendation system 100 includes a user terminal 110 and a computing device 200 .

[0034] The user terminal 110 is the terminal device used by the user, which may specifically be a personal computer such as a desktop computer, a notebook computer, or a m...

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Abstract

The invention discloses a content recommendation method, computing equipment and a storage medium. The method comprises the steps of obtaining current and historical click times and current and historical display times of each content in a content set, summing the current click times and the historical click times to obtain a first statistical value, summing the current display times and the historical display times, and subtracting the first statistical value to obtain a second statistical value; generating beta distribution based on the first statistical value and the second statistical value, and generating a random number based on the beta distribution as a first score of the content; when a request is received, obtaining a candidate set from the content set according to a predetermined recall strategy; for each content in the candidate content set, estimating a click probability of the user to the content based on the user feature and the content feature, and taking the click probability as a second score of the content; and performing weighted summation on the first score and the second score of the content to obtain a recommended score of the content, and selecting a predetermined number of contents from the candidate set based on the recommended score to serve as recommended contents.

Description

technical field [0001] The present invention relates to the field of the Internet, in particular to a content recommendation method, a computing device and a storage medium. Background technique [0002] With the rapid development of information technology and Internet technology, more and more users obtain network information through various computer devices (such as phone, pad, pc, etc.), and various information resources on the network are also growing explosively. People have gradually moved from an era of information scarcity to an era of information overload. In this era, both information consumers and information producers have encountered great challenges: as an information consumer, it is very difficult to find the information they are interested in from a large amount of information; as an information producer, How to make the information produced by oneself stand out and attract the attention of the majority of users is also a very difficult thing. [0003] In v...

Claims

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Application Information

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IPC IPC(8): G06F16/958G06F16/9538G06F16/9535
CPCG06F16/958G06F16/9538G06F16/9535
Inventor 陈积飞蔡建山
Owner BEIJING QIERBULAITE TECH
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