Snowflake inc. (20240338577). GENERATING MACHINE-LEARNING MODEL FOR DOCUMENT EXTRACTION simplified abstract
Contents
GENERATING MACHINE-LEARNING MODEL FOR DOCUMENT EXTRACTION
Organization Name
Inventor(s)
Ganeshan Ramachandran Iyer of Redmond WA (US)
Tomasz Malisz of Bialystok (PL)
Mikolaj Niedbala of Poznan (PL)
Saurin Shah of Kirkland WA (US)
Jan Tomasz Topinski of Izabelin (PL)
GENERATING MACHINE-LEARNING MODEL FOR DOCUMENT EXTRACTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338577 titled 'GENERATING MACHINE-LEARNING MODEL FOR DOCUMENT EXTRACTION
Simplified Explanation: This patent application describes systems and methods for creating a machine-learning model that can extract information from electronic documents, which can be used in databases or document information extraction processes.
Key Features and Innovation:
- Generation of a machine-learning model for extracting information from electronic documents.
- Use of the ML model as a data object in database commands or document information extraction processes.
- Continuous running of the document information extraction pipeline.
Potential Applications: The technology can be applied in various industries such as finance, healthcare, legal, and research for automating information extraction from documents.
Problems Solved: The technology addresses the manual effort required for extracting information from electronic documents, improving efficiency and accuracy in data processing.
Benefits: The benefits of this technology include increased productivity, reduced errors, and faster data extraction from documents.
Commercial Applications: The technology can be commercially used in document management systems, data analytics platforms, and information retrieval tools for businesses.
Questions about the Technology: 1. How does this technology improve data extraction processes? 2. What are the potential limitations of using machine-learning models for document information extraction?
Frequently Updated Research: Stay updated on advancements in machine learning models for document information extraction and their applications in various industries.
Original Abstract Submitted
systems and methods for generating a machine-learning (ml) model for extracting information from one or more electronic documents, where the ml model can be used as a data object, which can be part of a database command or as part of a document information extraction process that is continuously running (e.g., document information extraction pipeline).
