Snowflake inc. (20240338521). INTELLIGENT HUMAN-IN-THE-LOOP VALIDATION DURING DOCUMENT EXTRACTION PROCESSING simplified abstract
Contents
INTELLIGENT HUMAN-IN-THE-LOOP VALIDATION DURING DOCUMENT EXTRACTION PROCESSING
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)
INTELLIGENT HUMAN-IN-THE-LOOP VALIDATION DURING DOCUMENT EXTRACTION PROCESSING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338521 titled 'INTELLIGENT HUMAN-IN-THE-LOOP VALIDATION DURING DOCUMENT EXTRACTION PROCESSING
The abstract of this patent application describes systems and methods for processing electronic documents using machine-learning models to extract data points based on a schema, determining whether human validation is needed, and adding documents to a validation queue accordingly.
- Simplified Explanation:
This patent application outlines a process for using machine-learning models to extract data from electronic documents and deciding if human validation is required before adding the document to a validation queue.
- Key Features and Innovation:
- Processing electronic documents using machine-learning models - Extracting data points based on a schema - Determining the need for human validation - Adding documents to a validation queue as needed
- Potential Applications:
- Document processing automation - Data extraction from various sources - Quality control in data extraction processes
- Problems Solved:
- Streamlining data extraction from electronic documents - Improving accuracy in extracting data points - Efficiently managing human validation processes
- Benefits:
- Increased efficiency in data extraction - Improved accuracy in extracting data points - Enhanced quality control in document processing
- Commercial Applications:
Title: Automated Document Processing System This technology can be used in industries such as finance, legal, and healthcare for automating document processing tasks, improving data extraction accuracy, and enhancing overall efficiency in document management processes.
- Questions about the Technology:
1. How does this technology improve the accuracy of data extraction from electronic documents? - The technology uses machine-learning models to extract data points based on a schema, leading to more accurate results compared to manual extraction methods.
2. What are the potential challenges in implementing this technology in different industries? - Some challenges may include adapting the schema to different document formats and ensuring the machine-learning models are trained effectively for accurate data extraction.
Original Abstract Submitted
systems and methods for: processing a current electronic document, using a set of machine-learning (ml) models, to extract a set of values for a set of data points based on a schema, where the schema describes the set of data points to be extracted from electronic documents; determining whether to select the current electronic document for human validation based on the schema; and adding the current electronic document to a human validation queue in response to determining to select the current electronic document for human validation based on the schema.
