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    DETECTING DEVICE, DETECTING METHOD, MACHINE LEARNING DEVICE, MACHINE LEARNING METHOD, AND MACHINE LEARNING MODEL
    1.
    发明公开
    DETECTING DEVICE, DETECTING METHOD, MACHINE LEARNING DEVICE, MACHINE LEARNING METHOD, AND MACHINE LEARNING MODEL 审中-公开

    公开(公告)号：US20230419081A1

    公开(公告)日：2023-12-28

    申请号：US18339641

    申请日：2023-06-22

    Applicant: Rakuten Group, Inc.

    Inventor： Takashi TOMOOKA ,  Mitsuru Nakazawa

    IPC: G06N3/0455 ,  G06N3/084 ,  G06Q30/018

    CPC classification number: G06N3/0455 ,  G06N3/084 ,  G06Q30/0185

    Abstract: Disclosed herein is a detecting device including a second machine learning model provided for mutual learning together with a first machine learning model, the first machine learning model being subjected to machine learning so as to generate genuine or fraudulent article information having a plurality of modalities, and the second machine learning model being subjected to machine learning so as to discriminate whether article information having a plurality of modalities is genuine or not, an obtaining section configured to obtain article information having a plurality of modalities, and an estimating section configured to estimate whether the article information that is obtained by the obtaining section and has the plurality of modalities is genuine or not, by using the second machine learning model.

    LEARNING DEVICE, COMPUTER-READABLE INFORMATION STORAGE MEDIUM, AND LEARNING METHOD
    2.
    发明申请
    LEARNING DEVICE, COMPUTER-READABLE INFORMATION STORAGE MEDIUM, AND LEARNING METHOD 有权

    公开(公告)号：US20220207584A1

    公开(公告)日：2022-06-30

    申请号：US17645445

    申请日：2021-12-21

    Applicant: RAKUTEN GROUP, INC.

    Inventor： Mitsuru NAKAZAWA ,  Takashi TOMOOKA

    IPC: G06Q30/06 ,  G06N20/00

    Abstract: To determine whether product information provided from a seller is consistent, provided is a learning device including at least one processor, the at least one processor being configured to: acquire first and second product information from a storage in which a plurality of pieces of product information each including a plurality of pieces of item data relating to a product are stored in advance; generate third product information in which at least one piece of item data included in the first product information is replaced with the corresponding at least one piece of item data of the second product information; and cause a machine learning model to learn the third product information as inconsistent product information, wherein the machine learning model is configured to determine, when a piece of product information is input, whether the piece of product information is consistent.

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