International business machines corporation (20240312232). DOCUMENT INFORMATION EXTRACTION simplified abstract
Contents
DOCUMENT INFORMATION EXTRACTION
Organization Name
international business machines corporation
Inventor(s)
Han Qiao Yu of Shaanxi Province (CN)
DOCUMENT INFORMATION EXTRACTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240312232 titled 'DOCUMENT INFORMATION EXTRACTION
Simplified Explanation: This patent application describes a method for extracting information from documents using knowledge graphs and prompt-based learning. The method involves processing a document through optical character recognition (OCR), encoding text lines and bounding boxes into vectors, creating a knowledge graph, and using prompts to identify and extract relevant information.
- **Key Features and Innovation:**
- Utilizes OCR to extract text lines and bounding boxes from documents. - Encodes text lines and bounding boxes into semantic and position vectors. - Generates a knowledge graph using fusion vectors. - Uses prompts to identify and extract information based on query key values. - Calculates confidence levels to output extraction information.
- **Potential Applications:**
- Document analysis and information extraction. - Data mining and knowledge discovery. - Natural language processing and semantic search.
- **Problems Solved:**
- Efficient extraction of information from documents. - Improved accuracy in identifying and extracting relevant data. - Streamlined document processing and analysis.
- **Benefits:**
- Enhanced document understanding and information retrieval. - Increased efficiency in data extraction and analysis. - Facilitates automated document processing and knowledge extraction.
- **Commercial Applications:**
- This technology can be applied in industries such as legal, finance, healthcare, and research for document analysis, data extraction, and knowledge discovery.
- **Prior Art:**
- Researchers and practitioners in the fields of natural language processing, document analysis, and knowledge graphs may have relevant prior art related to this technology.
- **Frequently Updated Research:**
- Stay updated on advancements in OCR technology, knowledge graph applications, and document analysis methods for continuous improvement in information extraction processes.
Questions about Document Information Extraction using Knowledge Graphs and Prompt-based Learning:
1. *How does the method in this patent application differ from traditional document analysis techniques?*
- The method in this patent application combines OCR, knowledge graphs, and prompt-based learning to extract information from documents, offering a more advanced and efficient approach compared to traditional techniques.
2. *What are the potential challenges in implementing this technology in real-world applications?*
- Implementing this technology may require integration with existing document processing systems, ensuring scalability, and addressing potential issues related to data privacy and security.
Original Abstract Submitted
an embodiment for a method of extracting information from documents using knowledge graphs and prompt-based learning. the embodiment may receive a document and perform optical character recognition (ocr) to obtain ocr text lines and associated bounding boxes. the embodiment may encode each of the obtained ocr text lines into semantic vectors and each of the associated bounding boxes into position vectors to generate a knowledge graph using fusion vectors derived therefrom. the embodiment may receive a query including a key value. the embodiment may identify a series of candidate nodes including a series of most similar nearby nodes positioned near a first node associated with the key value. the embodiment may generate prompt template to determine closeness of the candidate nodes to the key value and calculate associated confidence levels. the embodiment may output extraction information associated with the candidate node having a highest calculated confidence level.
