Training method, recommendation method, device, server and medium of recommendation model

A technology of models and training samples, applied in the field of devices, servers and storage media, recommended model training methods, and recommended methods, can solve the problem of low flexibility of recommended models, achieve the effect of self-updating and improving flexibility

Active Publication Date: 2022-07-22
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 disclosure provides a training method, recommendation method, device, server, and storage medium for a recommendation model, so as to at least solve the problem of low flexibility of the recommendation model trained in related technologies

Method used

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  • Training method, recommendation method, device, server and medium of recommendation model
  • Training method, recommendation method, device, server and medium of recommendation model
  • Training method, recommendation method, device, server and medium of recommendation model

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Embodiment Construction

[0055] In order to make those skilled in the art 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 with reference to the accompanying drawings.

[0056] It should be noted that the terms "first", "second" and the like in the description and claims of the present disclosure and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate circumstances so 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 illustrative examples below are not intended to represent all implementations consistent with this disclosure. Rather, they are merely examples of apparatus and methods co...

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Abstract

The present disclosure relates to a training method, recommendation method, device, server and storage medium of a recommendation model. The training method of the recommendation model includes: obtaining training sample data; the training sample data includes sample account features, sample information features, and the actual access results of the sample account for the sample recommendation information; inputting the sample account features and sample information features into the recommendation model to be trained , obtain the predicted access result of the sample account for the sample recommendation information; based on the predicted access result and the actual access result, determine the value of the first loss function, and, based on the actual value and expected value of the gating parameter, determine the value of the second loss function; Based on the value of the first loss function and the value of the second loss function, a total loss value is determined; based on the total loss value, the recommendation model and gating parameters are updated to obtain a trained recommendation model. The present disclosure can realize autonomous update of gating parameters, so that the flexibility of the trained recommendation model can be improved.

Description

technical field [0001] The present disclosure relates to the technical field of information recommendation, and in particular, to a training method, recommendation method, device, server and storage medium of a recommendation model. Background technique [0002] With the development of information recommendation technology, there is a technology that uses neural network model to achieve information recommendation. By training the recommendation model, when recommending information to users, the characteristics of the recommended information and the user's characteristics can be input into the model. , the model outputs the probability of users accessing each recommendation information, so as to provide users with recommendation information with a high degree of fit. [0003] In the related art, in the current recommendation model, after the characteristics of the recommendation information and the characteristics of the user are obtained, the above-mentioned characteristics ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/08G06F16/958
CPCG06N3/08G06F16/958G06N3/048
Inventor 贾纪元李吉祥廖超杨森
Owner BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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