Automated Web Table Data Enrichment via Open Database Entity Matching
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Solution Overview
Problem
The abundance of information on the Internet makes it time-consuming to locate and process relevant data for presentations or Interactive Infographics, as existing methods require manual searching and lack efficient data enrichment.
Innovation Solution
A computer-implemented method that receives a table of plain text entries, matches them with entity tags from an open access database, and enriches the data by linking relevant information, allowing for automated context provision and data enrichment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual searching and processing methods are used to locate relevant information in large-scale open databases, then information can be found and incorporated into presentations or Interactive Infographics, but the time and effort required increases exponentially
Solution Approach 1:
The patent replaces manual mechanical searching and processing with automated computational systems. The system automatically scrapes tables from web pages, extracts entities, matches them with entity tags from open databases, and enriches the data without human intervention, thus substituting manual effort with automated information processing mechanisms
Solution Approach 2:
The system performs self-service by automatically enriching scraped table data with relevant information from open databases. The automated entity recognition, matching, and data enrichment processes occur without requiring manual searching or processing, allowing the system to serve itself in locating and incorporating relevant information
2Loss of information
If relevant information is found through manual searching, then it can be used in creating presentations or Interactive Infographics, but the processing complexity and time required increases
Solution Approach 1:
The patent replaces complex manual processing operations with automated computational processes. The system automatically performs entity recognition, extracts entities from scraped tables, matches them with entity tags from open databases, and enriches the data, thereby substituting complex manual processing with streamlined automated operations
Solution Approach 2:
The system extracts only the relevant entities and information needed from the scraped tables and open databases. By focusing on extracting specific entities rather than processing all information manually, the system reduces processing complexity while maintaining information relevance
3Quantity of substance
If more information is added to the Internet, then the availability of reference material increases, but the time and effort required to search through the information increases exponentially
Solution Approach 1:
The patent replaces manual information processing with automated systems that can efficiently handle large volumes of data. The automated scraping, entity recognition, and data enrichment processes enable the system to process increasing amounts of information from the Internet without a corresponding increase in time or effort
Solution Approach 2:
The system changes the parameter of information processing from manual to automated, enabling it to scale with the increasing quantity of information available on the Internet. The automated processes maintain constant processing efficiency regardless of the volume of information being handled
Data Source
AI summary
Techniques are described for importing data from a web page and enriching the imported data. While presenting a web page on a web browser, an input can be received to select an area of the web page. Tables that correspond to the selected area can be imported into a dataset as plain text. Tables imported in this manner can be verified and subsequently enriched. Data enrichment can include providing context to an entry. Data enrichment can also include associating or importing related data into the table from an open access database.