International business machines corporation (20240119093). ENHANCED DOCUMENT INGESTION USING NATURAL LANGUAGE PROCESSING simplified abstract
Contents
- 1 ENHANCED DOCUMENT INGESTION USING NATURAL LANGUAGE PROCESSING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ENHANCED DOCUMENT INGESTION USING NATURAL LANGUAGE PROCESSING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
ENHANCED DOCUMENT INGESTION USING NATURAL LANGUAGE PROCESSING
Organization Name
international business machines corporation
Inventor(s)
Susan Hallen of Chicago IL (US)
Rose Fleischman of Poughkeepsie NY (US)
[[:Category:Alan Daet Mej�a Villase�or of Guadalajara (MX)|Alan Daet Mej�a Villase�or of Guadalajara (MX)]][[Category:Alan Daet Mej�a Villase�or of Guadalajara (MX)]]
Diane Helen Wasserstrom of Poughkeepsie NY (US)
ENHANCED DOCUMENT INGESTION USING NATURAL LANGUAGE PROCESSING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240119093 titled 'ENHANCED DOCUMENT INGESTION USING NATURAL LANGUAGE PROCESSING
Simplified Explanation
The abstract describes a method for enhanced document ingestion using natural language processing, where terms unknown to one model are identified and compared to terms known to another model for improved processing.
- Identification of unknown terms in a document using a natural language processing model
- Comparison of unknown terms to known terms from another natural language processing model
- Reprocessing of the document using the second model if matching terms are found
Potential Applications
This technology could be applied in various industries such as information retrieval, data analysis, and content management systems.
Problems Solved
This technology helps in improving the accuracy and efficiency of document processing by leveraging multiple natural language processing models.
Benefits
The benefits of this technology include enhanced document understanding, improved data extraction, and increased automation of document processing tasks.
Potential Commercial Applications
One potential commercial application of this technology could be in developing advanced document management systems for businesses.
Possible Prior Art
Prior art in this field may include existing natural language processing techniques for document analysis and information extraction.
Unanswered Questions
How does this method handle documents in multiple languages?
The abstract does not specify how the method deals with documents that contain terms in languages other than the ones the natural language processing models are trained on.
What is the computational overhead of reprocessing documents with a different model?
The abstract does not address the potential increase in computational resources required to reprocess documents using a different natural language processing model.
Original Abstract Submitted
methods, systems, and computer program products for enhanced document ingestion using natural language processing are provided herein. a computer-implemented method includes identifying, within a first document, terms unknown to a first natural language processing model by processing the first document using the first natural language processing model; identifying, within a second document, terms known to a second natural language processing model by processing the second document using the second natural language processing model; comparing the terms unknown to the first natural language processing model to the terms known to the second natural language processing model; and upon determining that at least one of the terms unknown to the first natural language processing model matches at least one of the terms known to the second natural language processing model, reprocessing the first document using the second natural language processing model.
