The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 21, 2023

Filed:

Jul. 04, 2019
Applicant:

China Unionpay Co., Ltd., Shanghai, CN;

Inventors:

Yu Wang, Shanghai, CN;

Xuetao Qiu, Shanghai, CN;

Sishuang Wan, Shanghai, CN;

Xiaohan She, Shanghai, CN;

Yang Wang, Shanghai, CN;

Qi Zhang, Shanghai, CN;

Zhijun Fei, Shanghai, CN;

Assignee:

CHINA UNIONPAY CO., LTD., Shanghai, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); G06F 16/35 (2019.01); G06F 16/36 (2019.01); G06F 40/117 (2020.01); G06F 40/30 (2020.01);
U.S. Cl.
CPC ...
G06F 16/35 (2019.01); G06F 16/36 (2019.01); G06F 40/117 (2020.01); G06F 40/30 (2020.01);
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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