Table Generation from Print-Ready Documents via Wrapping Region Scoring
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Solution Overview
Problem
Print-ready digital source documents, such as XPS, RTF, and PDF, contain unstructured data that is difficult to access and manipulate, making it challenging to generate tables and analyze data efficiently.
Innovation Solution
A method is provided to automatically generate tables from print-ready digital source documents by identifying text fragments, calculating scores to determine block types, and organizing data into tabular format using wrapping regions and aggregation algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If data is stored in print-ready digital source documents with fixed spatial coordinates, then the document layout stability is improved, but the data accessibility and ease of manipulation deteriorates
Solution Approach 1:
The patent introduces an intermediary processing system that acts as a mediator between the fixed-layout print-ready document and the user's data manipulation needs. The system extracts text fragments with spatial coordinates, calculates wrapping regions, determines block types through scoring, and generates tabular representations. This intermediary layer preserves the original document's fixed layout while providing accessible, manipulable data structures to users.
2Manufacturing precision
If data is organized in unstructured format on rendered pages, then the document printing fidelity is improved, but the data analysis efficiency deteriorates
Solution Approach 1:
The patent segments the unstructured document content into discrete text fragments with spatial coordinates, then groups them into wrapping regions and blocks based on spatial relationships. This segmentation enables the system to process and analyze specific portions of data efficiently while maintaining the overall document structure for printing fidelity.
Solution Approach 2:
The patent transforms data from unstructured spatial coordinates into structured tabular format by changing the organizational parameters. It calculates tabular scores, narrative scores, and label scores to determine block types, then reorganizes text fragments into rows and columns. This parameter transformation maintains the semantic meaning while enabling efficient data analysis.
3Extent of automation
If automatic table generation is implemented, then the user interaction requirement is reduced, but the system complexity increases
Solution Approach 1:
The patent employs parameter-based classification to automate table generation. It calculates multiple scores (tabular score, narrative score, label score) based on spatial coordinates, text content, and wrapping region properties to automatically determine block types. This parameter-driven approach enables high-level automation through systematic, rule-based decision-making rather than complex heuristic algorithms.
Data Source
AI summary
Systems and methods are provided for generating tables from print-ready digital source documents. A document is received and one or more text fragments are identified on a rendered page of the document. A wrapping region collection is generated, comprising one or more wrapping regions. A tabular, narrative and label score is generated for each wrapping region. A block type is assigned to each wrapping region based on the scores. A wrapping region group and a block set are generated. One or more tables are generated based on text fragments corresponding to one of the one or more blocks. The text fragments are organized into corresponding fields of the one or more tables.