MERCHANT AUTHENTICITY VERIFICATION SYSTEM AND METHOD BASED ON STREET VIEW IMAGE RECOGNITION

    公开(公告)号:US20250156881A1

    公开(公告)日:2025-05-15

    申请号:US18838663

    申请日:2022-08-19

    Abstract: The present disclosure relates to a merchant authenticity verification system and method. The system comprises: a street view roaming module that calculates a translation scale for translating coordinates of an image acquisition point, calculates the coordinates of the image acquisition point based on the translation scale, and interacts with the street view image system to obtain a corresponding street view image based on the coordinates of the image acquisition point; an image comparison module that matches the merchant storefront image obtained with the street view image obtained from the street view roaming module to calculate merchant image similarity; a character recognition module for recognizing a merchant name from the street view image obtained from the street view roaming module; and a text comparison module for matching the merchant name recognized with the merchant name obtained from the merchant information platform to calculate merchant name similarity, and determining whether the merchant name similarity reaches a specified threshold, where in the case that the merchant name similarity reaches the specified threshold, merchant authenticity verification is successful. According to the present disclosure, the accuracy of merchant verification can be improved.

    Method and device for matching semantic text data with a tag, and computer-readable storage medium having stored instructions

    公开(公告)号:US11586658B2

    公开(公告)日:2023-02-21

    申请号:US17260177

    申请日:2019-07-04

    Abstract: A method for matching semantic text data with tags. The method includes: pre-processing multiple semantic text data to obtain original corpus data comprising multiple semantic independent members; determining the degree of association between any two of the multiple semantic independent members according to a reproduction relationship of the multiple semantic independent members in a natural text, determining a theme corresponding to the association according to the degree of association between any two, and thus determining a mapping probability relationship between the multiple semantic text data and the theme; selecting one of the multiple semantic independent members corresponding to the association as a tag of the theme, and mapping the multiple semantic text data to the tag according to the determined mapping probability relationship between the multiple semantic text data and the theme; and taking the determined mapping relationship between the multiple semantic text data and the tag as a supervision material, and matching the unmapped semantic text data with the tag according to the supervision material.

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