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A click rate prediction method and device

A click-through rate and preset technology, applied in the network field, can solve problems such as error-prone, inaccurate click-through rate of videos to be recommended, few user category features, etc., and achieve the effect of improving accuracy

Inactive Publication Date: 2019-06-07
XIAMEN MEITUZHIJIA TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, when analyzing the user's historical behavior, the user's category features are less, resulting in inaccurate prediction of the click-through rate of the video to be recommended, and errors are prone to occur

Method used

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  • A click rate prediction method and device
  • A click rate prediction method and device

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Embodiment Construction

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments.

[0042] figure 1 It is a schematic flowchart of a method for predicting click rate provided by an embodiment of the present invention. The execution device of the method may be a terminal such as a server, a computer, a mobile phone, and a tablet computer, which is not specifically limited in this embodiment of the present invention.

[0043] Such as figure 1 As shown, the method includes:

[0044] Step 101. Obtain historical playback behavior data and candidate video data of candidate users.

[0045]Specifically, candidate users can be selected a...

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Abstract

The invention provides a click rate prediction method and device, and relates to the technical field of networks. The method comprises: acquiring historical playing behavior data and candidate video data of candidate users; According to the historical playing behavior data and the candidate video data of the candidate user, extracting input data of each module of a preset multi-mode model, and according to the input data, performing training through each module of the preset multi-mode model to obtain a video click rate pre-estimation model; And obtaining to-be-recommended user data and to-be-recommended video data, and obtaining a click rate prediction value of clicking the to-be-recommended video by the to-be-recommended user through the video click rate prediction model. Wherein the input data comprises the interest information of the candidate user, the feedback information of the candidate video and the interaction information of the candidate video and the candidate user; and thevideo click rate prediction model is obtained through training of the multi-mode model, so that the video click rate prediction value is closer to the real condition of clicking the video by the user, and the accuracy of predicting the to-be-recommended video click rate is improved.

Description

technical field [0001] The present invention relates to the field of network technology, in particular, to a click rate prediction method and device. Background technique [0002] With the development of network technology, on the video platform, due to the complexity of the attributes of the video itself and the large amount of interaction between users and the video, a large amount of data will be generated. It is very important to use these data to predict the video and improve the click rate of users. of. [0003] In related technologies, when predicting the click-through rate of a recommended video, the user's historical playback records are mainly considered, and the user's interest and user interaction characteristics are analyzed based on the user's historical behavior to estimate the click-through rate of the video to be recommended. [0004] However, when analyzing the user's historical behavior, the user's category features are few, which leads to inaccurate pred...

Claims

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Application Information

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IPC IPC(8): H04N21/466H04N21/442H04N21/258H04N21/25H04N17/00
Inventor 蒋文瑞杨海钦蔡淇森游威朱逸
Owner XIAMEN MEITUZHIJIA TECH
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