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:
Jan. 02, 2024

Filed:

Apr. 12, 2019
Applicant:

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

Inventors:

Wei Zhao, Shenzhen, CN;

Yabing Feng, Shenzhen, CN;

Yu Liao, Shenzhen, CN;

Junbin Lai, Shenzhen, CN;

Haixia Chai, Shenzhen, CN;

Xuanliang Pan, Shenzhen, CN;

Lichun Liu, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 18/23 (2023.01); G06F 18/24 (2023.01); G06F 18/2115 (2023.01);
U.S. Cl.
CPC ...
G06F 18/217 (2023.01); G06F 18/214 (2023.01); G06F 18/2115 (2023.01); G06F 18/2148 (2023.01); G06F 18/2155 (2023.01); G06F 18/23 (2023.01); G06F 18/24 (2023.01);
Abstract

A data processing method and device are provided. The method includes: extracting a plurality of data sets from unlabeled data; and for each data set, creating a plurality of sample sets by assigning labels to data samples in the data set, respectively training, for each sample set created from the data set, a classifier by using the sample set and labeled data, obtaining a sample set that corresponds to a trained classifier with the highest performance, and adding the obtained sample set to a candidate training set. Each sample set includes the first preset number of data samples with respective labels, the labels of the data samples in each sample set constitutes a label combination, and label combinations corresponding to different sample sets are different from each other. The method also includes adding a second preset number of sample sets in the candidate training set to the labeled data.


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