Unstructured Document Structure Identification via Geometric Analysis
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Solution Overview
Problem
Existing document reconstruction methods are inefficient and resource-intensive, particularly on handheld devices, as they rely on computation and memory-intensive procedures like cluster analysis, making it challenging to effectively define structured documents from unstructured ones, especially on devices with limited resources.
Innovation Solution
The method involves analyzing unstructured documents to identify geometric attributes and relationships between primitive elements, such as words, paragraphs, and tables, by using techniques like density clustering and hierarchical profiling to define structural elements and enhance user interaction, while optimizing memory and processing usage through efficient data structures and cluster analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional cluster analysis is used for document reconstruction, then document structure can be identified, but computation and memory resources are excessively consumed
Solution Approach 1:
The patent segments the document reconstruction process into distinct phases: geometric analysis phase (identifying boundaries, regions, and spatial relationships) and structural element definition phase (creating logical groupings based on geometric attributes). This segmentation allows the system to process documents in manageable steps, reducing memory overhead compared to traditional cluster analysis that requires loading all data simultaneously.
Solution Approach 2:
The patent introduces geometric attributes as an intermediary representation between raw primitive elements and final structural elements. By first extracting geometric properties (boundaries, regions, spatial relationships) and then using these as intermediaries to define structural elements, the system avoids the computational intensity of direct cluster analysis while maintaining reconstruction accuracy.
2Loss of information
If full document reconstruction is performed, then complete structural understanding is achieved, but processing time increases significantly
Solution Approach 1:
The patent performs preliminary geometric analysis to identify boundaries, regions, and spatial relationships before proceeding to structural element definition. By pre-processing the document to extract geometric attributes and organize primitive elements spatially, the system reduces the complexity of subsequent structural analysis, enabling faster overall processing while maintaining complete structural information.
3Manufacturing precision
If detailed geometric analysis is performed on all primitive elements, then accurate structural elements are defined, but memory usage increases
Solution Approach 1:
The patent extracts only the essential geometric attributes (boundaries, regions, spatial relationships) needed for structural element definition, rather than processing all possible properties of primitive elements. This selective extraction reduces memory requirements while maintaining sufficient accuracy for defining tables, paragraphs, columns, and other structural elements.
Data Source
AI summary
Some embodiments provide a method of analyzing an unstructured document. The method receiving the unstructured document that includes a number of primitive graphic elements, each of which is defined as a single object in the unstructured document. The unstructured document has a drawing order that indicates the order in which the primitive graphic elements are drawn when the unstructured document is displayed. The method identifies positional relationships between successive primitive graphic elements in the drawing order. Based on the positional relationships, the method defines a single structural graphic element from several of the primitive graphic elements.