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:
Nov. 15, 2022

Filed:

Jul. 03, 2019
Applicant:

Baidu Online Network Technology (Beijing) Co., Ltd., Beijing, CN;

Inventors:

Mingming Sun, Beijing, CN;

Xu Li, Beijing, CN;

Ping Li, Beijing, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 40/151 (2020.01); G06F 40/126 (2020.01); G06N 5/02 (2006.01); G06N 20/20 (2019.01); G06K 9/62 (2022.01); G06F 17/18 (2006.01);
U.S. Cl.
CPC ...
G06N 5/025 (2013.01); G06F 17/18 (2013.01); G06F 40/126 (2020.01); G06F 40/151 (2020.01); G06K 9/6215 (2013.01); G06K 9/6256 (2013.01); G06N 20/20 (2019.01);
Abstract

A method and an apparatus for generating a model are provided. The method includes: acquiring a sample set including sample sentences and labeling knowledge corresponding thereto; and selecting a sample from the sample set, and performing following training steps: inputting a sample sentence into a first initial model to generate first prediction knowledge corresponding to the sample sentence; inputting the first prediction knowledge into a second initial model to generate a first prediction sentence corresponding to the first prediction knowledge; inputting labeling knowledge into the second initial model to generate a second prediction sentence corresponding to the labeling knowledge; inputting the second prediction sentence into the first initial model to generate a second prediction knowledge corresponding to the second prediction sentence; determining a first reward signal; and training, using a reinforcement learning method based on the first reward signal to obtain a first model.


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