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. 15, 2026

Filed:

Aug. 11, 2022
Applicants:

Qingyi Fan, Shanghai, CN;

Accenture Global Solutions Limited, Dublin, IE;

Inventors:

Qingyi Fan, Shanghai, CN;

Qirun Chen, Dublin, IE;

Stephen Redmond, Dublin, IE;

Renata Sofia Pardal Dos Santos, Torres Vedras, PT;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/35 (2025.01); G06F 40/205 (2020.01); G06F 40/263 (2020.01); G06F 40/289 (2020.01); G06F 40/58 (2020.01);
U.S. Cl.
CPC ...
G06F 16/35 (2019.01); G06F 40/205 (2020.01); G06F 40/263 (2020.01); G06F 40/289 (2020.01); G06F 40/58 (2020.01);
Abstract

The present disclosure relates to a system, a method, and a product for topic discovery. The system includes a memory storing instructions; and a processor in communication with the memory. When the processor executes the instructions, the instructions are configured to cause the processor to: obtain text data, conduct pre-processing on the text data to obtain pre-processed text data, extract an entity list and a keyword list based on the pre-processed text data, generate an entity embedding list based on the entity list, clusterize the entity list based on the entity embedding list to obtain a plurality of entity clusters, each entity cluster comprising at least one entity, retrieve a co-occurring keyword list based on the plurality of entity clusters, the entity list, and the keyword list, and obtain a topic for each entity cluster of the plurality of entity clusters based on the co-occurring keyword list.


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