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. 17, 2024

Filed:

May. 31, 2022
Applicant:

Samsung Sds Co., Ltd., Seoul, KR;

Inventors:

Bong-Kyu Hwang, Seoul, KR;

Ju-Dong Kim, Seoul, KR;

Jae-Woong Yun, Seoul, KR;

Hyun-Jae Lee, Seoul, KR;

Hyun-Jin Choi, Seoul, KR;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/295 (2020.01); G06F 16/34 (2019.01); G06F 40/205 (2020.01); G06F 40/284 (2020.01); G06F 40/30 (2020.01);
U.S. Cl.
CPC ...
G06F 16/345 (2019.01); G06F 40/205 (2020.01); G06F 40/284 (2020.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01);
Abstract

An apparatus for training a document summarization model includes a token generation unit, a named entity recognition unit, and a model training unit. The token generation unit generates document tokens and summarization tokens. The named entity recognition unit assigns named entity token status to a summarization token, recognized as a named entity through NER, and assigns non-named entity token status to the other tokens. The model training unit obtains feature vectors by inputting the plurality of document tokens into an encoder inside a document summarization model, obtains a first loss related to the named entity token, a second loss related to the other tokens, and a total loss using a weighted value by inputting the feature vectors, the summarization tokens, the named entity token, and the non-named entity token into a decoder inside the document summarization model, and trains the document summarization model on the basis of the total loss.


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