INFORMATION RECOMMENDATION MODEL TRAINING METHOD AND RELATED DEVICE

WIPO Patent Application WO/2022/041979

A1

Disclosed in embodiments of the present application are an artificial intelligence-based information recommendation model training method and a related device. The method comprises: obtaining historical user behavior data of multiple product fields; using a generation model of a generative adversarial network to generate, according to the historical user behavior data, candidate sample data of product fields to be expanded of the multiple product fields, so as to generate a false sample to expand user behavior data;using each of the multiple product fields as a target product field, separately, and performing, by means of a discrimination model of the generative adversarial network, discrimination of true and false samples for a user on the candidate sample data of the target product field and user click sample data to obtain a discrimination result; and performing adversarial training on the generation model and the discrimination model according to the discrimination result to obtain a trained generative adversarial network,the trained generative adversarial network being used for determining an information recommendation model. The method can improve the training effect of a generation model and improve the accuracy of generation of a false sample, thereby further improving a recommendation effect.

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HAO XIAOBO (CN)
GE KAIKAI (CN)
LIU YUDAN (CN)
TANG LINYAO (CN)
XIE RUOBING (CN)
ZHANG XU (CN)
LIN LEYU (CN)

PCT/CN2021/101522

March 03, 2022

June 22, 2021

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TENCENT TECH SHENZHEN CO LTD (CN)

G06F16/9035; G06N3/08

CN111931062A	2020-11-13
CN106776873A	2017-05-31
CN111291274A	2020-06-16
CN111460130A	2020-07-28
CN106897464A	2017-06-27

SHENPAT INTELLECTUAL PROPERTY AGENCY (CN)

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