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. 24, 2023

Filed:

Nov. 27, 2019
Applicant:

Foundation of Soongsil University-industry Cooperation, Seoul, KR;

Inventors:

Young Tack Park, Seoul, KR;

Jagvaral Batselem, Seoul, KR;

Wan Gon Lee, Seoul, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06K 9/62 (2022.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06F 17/16 (2006.01); G06N 20/20 (2019.01); G06N 20/10 (2019.01); G06N 5/04 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6262 (2013.01); G06F 17/16 (2013.01); G06N 3/0454 (2013.01); G06N 3/084 (2013.01); G06N 5/046 (2013.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01);
Abstract

A triple verification method is provided. The triple verification method includes setting a triple having a source entity, a target entity, and a relation value between the source entity and the target entity by a setting unit, extracting a plurality of intermediate entities associated with the source entity and the target entity by the setting unit, defining a connection relation between the intermediate entity, the source entity, and the target entity and generating a plurality of connection paths connecting the source entity, the intermediate entity, and the target entity by a path generation unit, generating a matrix by embedding the plurality of connection paths into vector values by a first processing unit, calculating a feature map by performing a convolution operation on the matrix by a second processing unit, generating an encoding vector for each connection path by encoding the feature map by applying a bidirectional long short-term memory neural network (BiLSTM) technique by a third processing unit, and generating a state vector by summing the encoding vectors for each connection path by applying an attention mechanism and verifying the triple based on a similarity value between the relation value of the triple and the state vector by a determination unit.


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