International business machines corporation (20240104093). ENRICHING UNSTRUCTURED COMPUTER CONTENT WITH DATA FROM STRUCTURED COMPUTER DATA SOURCES FOR ACCESSIBILITY simplified abstract
Contents
- 1 ENRICHING UNSTRUCTURED COMPUTER CONTENT WITH DATA FROM STRUCTURED COMPUTER DATA SOURCES FOR ACCESSIBILITY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ENRICHING UNSTRUCTURED COMPUTER CONTENT WITH DATA FROM STRUCTURED COMPUTER DATA SOURCES FOR ACCESSIBILITY - 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 How does this technology handle privacy concerns related to extracting data from structured sources?
- 1.11 What are the potential limitations of this technology in terms of scalability and performance?
- 1.12 Original Abstract Submitted
ENRICHING UNSTRUCTURED COMPUTER CONTENT WITH DATA FROM STRUCTURED COMPUTER DATA SOURCES FOR ACCESSIBILITY
Organization Name
international business machines corporation
Inventor(s)
Michael Drzewucki of Woodbridge VA (US)
Elinna Shek of Ashburn VA (US)
Keith Gregory Frost of Delaware OH (US)
Christopher F. Ackermann of Fairfax VA (US)
Charles E. Beller of Baltimore MD (US)
ENRICHING UNSTRUCTURED COMPUTER CONTENT WITH DATA FROM STRUCTURED COMPUTER DATA SOURCES FOR ACCESSIBILITY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104093 titled 'ENRICHING UNSTRUCTURED COMPUTER CONTENT WITH DATA FROM STRUCTURED COMPUTER DATA SOURCES FOR ACCESSIBILITY
Simplified Explanation
The abstract describes a method for automatically annotating unstructured computer content with additional contextual information from structured computer data sources. This involves identifying data elements, extracting entities, querying structured data sources, generating natural language text, and annotating the content.
- Identifying data elements within unstructured computer content
- Matching extraction templates to the data elements
- Automatically extracting an entity from the data elements using the extraction templates
- Querying structured computer data sources using the extracted entity to identify a matching data record
- Extracting data from the data record and generating natural language text
- Automatically annotating the unstructured computer content with the additional contextual information by inserting the generated natural language text
Potential Applications
This technology could be applied in information retrieval systems, data analysis tools, and content management systems.
Problems Solved
This technology solves the problem of manually annotating unstructured computer content with contextual information, which can be time-consuming and error-prone.
Benefits
The benefits of this technology include improved organization and categorization of computer content, enhanced search capabilities, and increased efficiency in data processing.
Potential Commercial Applications
Potential commercial applications of this technology include software tools for data annotation, content enrichment services, and information extraction solutions.
Possible Prior Art
One possible prior art for this technology could be natural language processing techniques used in information retrieval systems and text mining applications.
Unanswered Questions
The article does not address how privacy concerns are addressed when extracting data from structured sources.
What are the potential limitations of this technology in terms of scalability and performance?
The article does not discuss the potential limitations of this technology in terms of scalability and performance.
Original Abstract Submitted
a method for automatically annotating unstructured computer content associated with computer resources with additional contextual information from structured computer data sources is provided. the method may include, automatically identifying data elements within the unstructured computer content and matching extraction templates to the data elements. the method may further include automatically extracting an entity from the data elements using the extraction templates. the method may further include querying the structured computer data sources using the extracted entity to identify a data record in the structured computer data sources matching the entity. the method may further include extracting data from the data record and generating natural language text using the extracted data. the method may further include automatically annotating the unstructured computer content with the additional contextual information by inserting the generated natural language text into the unstructured computer content.
