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:
Oct. 24, 2023

Filed:

Mar. 24, 2021
Applicant:

Beijing Baidu Netcom Science and Technology Co., Ltd., Beijing, CN;

Inventors:

Huan Liu, Beijing, CN;

Mingquan Cheng, Beijing, CN;

Kunbin Chen, Beijing, CN;

Zhun Liu, Beijing, CN;

Bolei He, Beijing, CN;

Wei He, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/901 (2019.01); G06F 18/21 (2023.01); G06F 18/25 (2023.01); G06F 18/2132 (2023.01); G06F 40/30 (2020.01); G06T 7/00 (2017.01); G06V 30/413 (2022.01); G06V 30/40 (2022.01); G06V 30/18 (2022.01); G06V 30/19 (2022.01); G06V 10/82 (2022.01); G06V 30/10 (2022.01);
U.S. Cl.
CPC ...
G06F 16/901 (2019.01); G06F 18/217 (2023.01); G06F 18/253 (2023.01); G06F 40/30 (2020.01); G06T 7/0002 (2013.01); G06V 10/82 (2022.01); G06V 30/18057 (2022.01); G06V 30/19173 (2022.01); G06V 30/40 (2022.01); G06V 30/413 (2022.01); G06F 18/2132 (2023.01); G06T 2207/30168 (2013.01); G06T 2207/30176 (2013.01); G06V 30/10 (2022.01);
Abstract

Embodiments of the present disclosure disclose a method and apparatus for constructing a quality evaluation model, an electronic device and a computer-readable storage medium. A specific implementation mode of the method comprises: acquiring samples of knowledge contents; extracting statistical features, semantic features, and image features respectively from the samples of knowledge contents; and constructing a quality evaluation model for knowledge according to the statistical features, the semantic features, and the image features. On the basis of the prior art, this implementation mode additionally uses semantic features and image features of knowledge contents to construct a more accurate quality evaluation model based on multi-dimensional features that characterize the actual quality of a knowledge, which may well discover some brief but very useful summary knowledge in an enterprise and may recommend high-quality knowledge more accurately for employees in the enterprise.


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