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Live broadcast recommendation model training method, live broadcast recommendation method and related equipment

A model training and model technology, applied in the Internet field, can solve problems such as poor accuracy of recommended live broadcasts, and achieve the effect of avoiding poor accuracy of live broadcasts

Active Publication Date: 2022-05-06
BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present disclosure provides a live broadcast recommendation model training method, a live broadcast recommendation method, and related equipment, so as to at least solve the problem of poor accuracy in recommending live broadcasts in a live broadcast real-time recommendation scenario in related technologies

Method used

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  • Live broadcast recommendation model training method, live broadcast recommendation method and related equipment
  • Live broadcast recommendation model training method, live broadcast recommendation method and related equipment
  • Live broadcast recommendation model training method, live broadcast recommendation method and related equipment

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Embodiment Construction

[0134] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0135] It should be noted that the terms "first" and "second" in the specification and claims of the present disclosure and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein can be practiced in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consi...

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Abstract

The present disclosure relates to a live broadcast recommendation model training method, a live broadcast recommendation method, and related equipment. The live broadcast recommendation model training method includes: responding to a sample terminal's live broadcast recommendation request, acquiring characteristic information corresponding to a sample live broadcast to be displayed on the sample terminal, And acquiring the interactive information obtained based on the live broadcast of the sample; splicing the feature information corresponding to the live broadcast of the sample and the interactive information to obtain the target sample; training the preset neural network model based on the target sample, and A live broadcast recommendation model is obtained according to the neural network model at the end of the training; the live broadcast recommendation model is used to determine the probability of interaction between the target terminal and candidate live broadcasts in the live broadcast recommendation. The disclosure avoids the problem of poor live broadcast recommendation accuracy in live broadcast real-time recommendation scenarios caused by sample selection bias and training data sparseness.

Description

technical field [0001] The present disclosure relates to the technical field of the Internet, and in particular to a live broadcast recommendation model training method, a live broadcast recommendation method and related equipment. Background technique [0002] With the rapid development of the e-commerce live broadcast industry, the recommendation of products and other recommended objects through live broadcast has become a popular way of information transmission. [0003] In related technologies, a CTR (Click-Through-Rate, click-through rate) model and a CVR (Conversion Rate, conversion rate) model are trained respectively, and then the trained CTR model and CVR model are used for live broadcast recommendation. Among them, the CTR model is trained based on live display behavior data, which predicts the probability of users clicking on live display; the CVR model is trained based on user click behavior data on live display, which predicts the probability of users converting...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/06G06Q30/02G06N3/08G06N3/04
CPCG06Q30/0631G06Q30/0271G06Q30/0253G06Q30/0254G06Q30/0277G06N3/08G06N3/045
Inventor 黄兆楷
Owner BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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