Document Table Extraction Using Breakpoint Streaming and Spatial Parsing
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Solution Overview
Problem
Conventional methods struggle to efficiently identify and extract structured data from financial documents due to the complexity of spatially-aligned grid systems, leading to difficulties in applying sophisticated algorithms for table identification, segmentation, and parsing.
Innovation Solution
A platform, language, and database agnostic automatic table identification and extraction module that implements algorithms for high-speed processing, intelligent streaming, bounded recursive search, and low-level parsing to structure tables in structured triplets of index, column, and value, using processors and memory to identify breakpoints and align columns based on spatial overlap.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional approaches are used to identify and extract tables from financial documents, then the extraction process can be performed, but the processing speed is slow and computational complexity is high
Solution Approach 1:
The patent segments the document processing into distinct phases: breakpoint identification, table extraction, and spatial parsing. By dividing the computational task into smaller independent segments that can be processed separately and in parallel, the system reduces overall computational complexity while improving processing throughput and speed.
Solution Approach 2:
The patent performs preliminary breakpoint identification before table extraction. By pre-identifying potential table regions using simple pattern matching on breakpoints (such as repeated whitespace patterns), the system prepares the data structure in advance, reducing the computational burden during the actual table extraction and parsing phases.
2Measurement precision
If sophisticated algorithms are applied for table identification and segmentation, then extraction accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by using simplified breakpoint identification methods for initial table region detection, then applying more sophisticated spatial parsing algorithms only to the identified table regions. This selective application of algorithmic complexity maintains high extraction accuracy for actual tables while avoiding the time cost of applying complex algorithms to entire documents.
Solution Approach 2:
The patent implements local quality by applying different levels of processing intensity to different document regions. Table regions identified through breakpoint analysis receive intensive spatial parsing and alignment processing, while non-table regions are quickly skipped. This localized application of sophisticated algorithms maintains accuracy where needed while reducing overall processing time.
3Reliability
If the entire document is processed to identify tables, then all tables can be found, but the processing becomes inefficient for large documents
Solution Approach 1:
The patent extracts and processes only the essential breakpoint information from documents rather than analyzing every character and spatial coordinate. By extracting key structural markers (breakpoints indicating potential table boundaries) and processing only those regions, the system maintains complete table identification while dramatically improving processing efficiency for large documents.
Solution Approach 2:
The patent performs preliminary scanning to identify breakpoint patterns throughout the document before conducting detailed table extraction. This preliminary action creates an index of potential table regions that guides subsequent processing, ensuring no tables are missed while avoiding the inefficiency of processing the entire document at full detail.
Data Source
AI summary
Various methods and processes, apparatuses or systems, and media for automatic table identification and extraction in a document by utilizing one or more processors along with allocated memory are disclosed. The processor receives a variably sized document and streams content of the variably sized document line by line in a sliding window to identify breakpoints. The streaming is independent to the number of tables in the document, or length of the document, and the breakpoints identify start and end of a table. The processor also identifies and extracts a table within the document based on the breakpoints; implements spatially aware parsing algorithm for layout analysis, table constructions, and radial context search from the identified table; and automatically structures the table in structured triplets of index, column, and value that dictates a row, a column, and an entry value, respectively.