Multi-level List Detection Engine for Document Conversion
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Solution Overview
Problem
Existing document converters struggle to convert fixed format documents into flow format documents, particularly when complex elements like multi-level lists are involved, often prioritizing visual fidelity over flowability, resulting in limited output that requires substantial manual reconstruction.
Innovation Solution
A multi-level list detection engine that identifies and processes list elements in fixed format documents, creating dynamic multi-level list objects in flow format documents, which automatically update with user edits, by employing list identifier detection, grouping, level assignment, and post-processing operations to ensure accurate formatting and flowability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing document converters use base techniques to preserve visual fidelity of fixed format document layout, then layout accuracy is improved, but the flowability and editability of the output document deteriorates
Solution Approach 1:
The converter segments the document processing into distinct phases: layout analysis to capture visual fidelity, semantic interpretation to identify list structures, and flow format generation to create editable output. This segmentation allows each phase to optimize for its specific goal without compromising the others.
Solution Approach 2:
The patent introduces an intermediary semantic representation layer between the fixed format input and flow format output. This intermediate structure captures both the visual layout information and the semantic meaning of list elements, enabling accurate conversion to editable flow format while preserving the original document's intent.
2Stability of the object's composition
If existing document converters prioritize visual fidelity preservation, then layout consistency is improved, but the need for manual reconstruction increases
Solution Approach 1:
The converter performs self-service by automatically detecting list structures, determining appropriate flow format representations, and generating editable output documents. This automation eliminates the need for manual reconstruction of list elements, saving time while maintaining layout consistency through algorithmic analysis.
Solution Approach 2:
The patent applies preliminary semantic analysis and structure detection before generating the flow format output. By pre-identifying list elements, hierarchy levels, and formatting patterns in the fixed format document, the converter prepares the data in advance, enabling direct conversion to editable flow format without requiring subsequent manual intervention.
3Manufacturing precision
If existing document converters use basic physical layout elements for conversion, then visual fidelity is improved, but the complexity of manual editing increases
Solution Approach 1:
The patent transforms static visual layout representations into dynamic, editable flow format structures. By detecting semantic list patterns and converting them to native flow format list objects, the output document becomes dynamically editable with automatic renumbering and restructuring capabilities, greatly improving editing ease while preserving visual fidelity through accurate pattern recognition.
Solution Approach 2:
The converter changes the fundamental parameters of the document representation from fixed physical layout coordinates to flow format semantic structures. This parameter transformation enables the document to switch from a static visual snapshot to a dynamic, editable structure that maintains visual fidelity through intelligent conversion of list hierarchies and formatting patterns.
Data Source
AI summary
A multi-level list detection engine. The multi-level list detection engine detects text obtained from a fixed format document that is formatted as a static multi-level list and creates a dynamic multi-level list object in a flow format document. The resulting dynamic multi-level list object automatically updates as the end user edits the multi-level list in the flow format document. The multi-level list detection engine identifies list elements in the fixed format text based on the presence of a list identifier. The list elements are grouped into lists based on the properties of each list element relative to other list elements. List elements are then assigned to a list level based on the relative properties of the list elements within a list. Finally, level list assignments are verified and corrected, the levels are merged, as necessary, and the lists are consistently formatted as appropriate to create a final well-formed dynamic multi-level list object.