Invention Grant
- Patent Title: Table item information extraction with continuous machine learning through local and global models
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Application No.: US18331990Application Date: 2023-06-09
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Publication No.: US12080091B2Publication Date: 2024-09-03
- Inventor: Matthias Theodor Middendorf , Gisela Barbara Cäcilie Hammann , Carsten Peust
- Applicant: Open Text SA ULC
- Applicant Address: CA Halifax
- Assignee: OPEN TEXT SA ULC
- Current Assignee: OPEN TEXT SA ULC
- Current Assignee Address: CA Halifax
- Agency: SPRINKLE IP LAW GROUP
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06F16/22 ; G06F16/25 ; G06F16/93 ; G06F18/21 ; G06F40/174 ; G06F40/177 ; G06F40/186 ; G06F40/216 ; G06F40/274 ; G06N20/00 ; G06V30/19 ; G06V30/412 ; G06V30/414 ; G06V30/416

Abstract:
A bipartite application implements a table auto-completion (TAC) algorithm on the client side and the server side. A client module runs a local model of the TAC algorithm on a user device and a server module runs a global model of the TAC algorithm on a server machine. The local model is continuously adapted through on-the-fly training, with as few as one negative example, to perform TAC on the client side, one document at a time. Knowledge thus learned by the local model is used to improve the global model on the server side. The global model can be utilized to automatically and intelligently extract table information from a large number of documents with significantly improved accuracy, requiring minimal human intervention even on complex tables.
Public/Granted literature
- US20230334888A1 TABLE ITEM INFORMATION EXTRACTION WITH CONTINUOUS MACHINE LEARNING THROUGH LOCAL AND GLOBAL MODELS Public/Granted day:2023-10-19
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