Automated Table Population from Document Parsing
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Solution Overview
Problem
Manual entry of large datasets into tables is time-consuming and prone to human error.
Innovation Solution
Automated process for generating and populating tables by parsing documents to identify common elements, extracting header values, and aligning data values accordingly, allowing for efficient data entry without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual entry is used to populate tables, then data can be entered with human judgment and correction, but the process is time-consuming and prone to human error
Solution Approach 1:
The system performs automatic table generation and population without human intervention. The processor autonomously parses documents, identifies common elements, generates table structures, extracts data values, and populates tables, eliminating the need for manual data entry while maintaining high accuracy through automated parsing and matching algorithms
Solution Approach 2:
The manual mechanical process of data entry is replaced with an automated computational system. The processor uses document parsing, pattern recognition, and data extraction algorithms to automatically populate tables, substituting human manual operations with automated information processing
2Productivity
If automated table generation is implemented, then efficiency increases and human error reduces, but the device complexity increases
Solution Approach 1:
The processor performs multiple functions within a single integrated system: document parsing, common element identification, table structure generation, data value extraction, and table population. This multi-functional approach consolidates what could be separate complex systems into one unified automated table generation system
Solution Approach 2:
The automated table generation process is divided into distinct operational stages: parsing documents to identify common elements, generating table structures from those elements, extracting data values from documents, and populating tables with extracted data. This segmentation makes the complex automated system more manageable and implementable
Data Source
AI summary
Automatically generating and/or populating a table is described. In some embodiments, in response to receiving an indication to include data from a set of documents in a table, each of at least a subset of documents included in the set of documents is parsed to identify a set of one or more common elements, a table with a structure derived from at least a subset of the set of common elements is generated, and an entry for each of one or more documents in the set of documents included in the table is populated with data values extracted from the content of that document.