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:
Sep. 07, 2021

Filed:

May. 30, 2019
Applicant:

Tencent Technology (Shenzhen) Company Limited, Guangdong, CN;

Inventors:

Xiao ming Xiang, Shenzhen, CN;

Fei Wang, Shenzhen, CN;

Ling Liao, Shenzhen, CN;

Xiao bing Feng, Shenzhen, CN;

Hao Xu, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); G06N 3/08 (2006.01); G06F 40/30 (2020.01); G06F 40/284 (2020.01); G06F 16/9032 (2019.01); G06F 16/332 (2019.01); G06F 16/33 (2019.01); G10L 15/22 (2006.01); G10L 15/18 (2013.01);
U.S. Cl.
CPC ...
G06F 16/00 (2019.01); G06F 16/3329 (2019.01); G06F 16/3344 (2019.01); G06F 16/90332 (2019.01); G06F 40/284 (2020.01); G06F 40/30 (2020.01); G06N 3/08 (2013.01); G10L 15/1815 (2013.01); G10L 15/22 (2013.01);
Abstract

A semantic extraction method based on a natural language is provided. In a character library based on a single-character granularity, a character of an input natural language is queried, to obtain first semantic vectors representing semantic descriptions of the character. Candidate semantic intentions corresponding to second semantic vectors and weight vectors corresponding to the candidate semantic intentions are obtained, wherein the second semantic vectors are obtained by using a neural network and correspond to different permutations and combinations of the first semantic vectors. A candidate semantic intention is selected as a final semantic intention of the natural language based on a preset condition, and key information is obtained corresponding to the final semantic intention according to a weight vector corresponding to the final semantic intention.


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