View source for International business machines corporation (20240202358). SMART IDENTIFICATION OF INDICATOR TEXT WITH FULL-TEXT SEARCH OR OPTIMIZED DOCUMENT ANALYSIS simplified abstract

=SMART IDENTIFICATION OF INDICATOR TEXT WITH FULL-TEXT SEARCH OR OPTIMIZED DOCUMENT ANALYSIS=


==Organization Name==

[[:Category:international business machines corporation|international business machines corporation]]


[[Category:international business machines corporation]]

==Inventor(s)==

[[:Category:Thomas Hampp-bahnmueller of Stuttgart (DE)|Thomas Hampp-bahnmueller of Stuttgart (DE)]][[Category:Thomas Hampp-bahnmueller of Stuttgart (DE)]]

[[:Category:Michael Baessler of Bempflingen (DE)|Michael Baessler of Bempflingen (DE)]][[Category:Michael Baessler of Bempflingen (DE)]]

[[:Category:Yannick Saillet of Stuttgart (DE)|Yannick Saillet of Stuttgart (DE)]][[Category:Yannick Saillet of Stuttgart (DE)]]

==SMART IDENTIFICATION OF INDICATOR TEXT WITH FULL-TEXT SEARCH OR OPTIMIZED DOCUMENT ANALYSIS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240202358 titled 'SMART IDENTIFICATION OF INDICATOR TEXT WITH FULL-TEXT SEARCH OR OPTIMIZED DOCUMENT ANALYSIS

The abstract describes a method for optimizing unstructured document analysis by operating a document system with a full-text index, identifying documents with specific data elements, selecting a sample of documents, determining data elements in the sample, creating an indicator context expression, generating a search query using the indicator context expression, and identifying compliant documents in the system.

*Simplified Explanation:
The patent application outlines a process to improve the analysis of unstructured documents by efficiently identifying and retrieving relevant information based on specific data elements.

*Key Features and Innovation:
- Utilizing a full-text index in a document system
- Identifying documents with specific data elements
- Creating indicator context expressions for data elements
- Generating search queries for efficient retrieval of information

*Potential Applications:
- Information retrieval systems
- Data mining and analysis tools
- Document management software

*Problems Solved:
- Enhancing the efficiency of unstructured document analysis
- Improving information retrieval accuracy
- Streamlining data mining processes

*Benefits:
- Increased productivity in analyzing large volumes of unstructured data
- Enhanced accuracy in retrieving relevant information
- Improved decision-making based on extracted data

*Commercial Applications:
Optimizing unstructured document analysis technology can be applied in various industries such as legal, healthcare, finance, and research for efficient data extraction and analysis.

*Prior Art:
Researchers can explore existing patents and publications related to document analysis, data mining, and information retrieval systems to understand the prior art in this field.

*Frequently Updated Research:
Stay updated on advancements in natural language processing, machine learning, and artificial intelligence to enhance the capabilities of unstructured document analysis technology.

Questions about unstructured document analysis:
1. How does this technology improve the efficiency of data extraction from unstructured documents?
2. What are the potential challenges in implementing this method in real-world applications?


==Original Abstract Submitted==

several aspects for optimizing unstructured document analysis comprise operating a document system, where the document system comprises a plurality of documents comprising unstructured content and a full-text index; receiving a request to identify documents comprising a type of data elements; selecting a sample out of the plurality of documents; determining data elements of the type in the sample of documents; determining an indicator context expression for the type of data elements out of the determined data elements of the type; determining a query for searching, using a search engine, the full-text index using the indicator context expression; and determining the documents in the document system being compliant to the determined query.



[[Category:G06F21/62]]
[[Category:G06F16/31]]
[[Category:G06F16/332]]
[[Category:CPC_G06F21/6245]]