Document Element Search Using Rule-Based Data Groups
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Solution Overview
Problem
Managing hierarchical document structures during creation and editing is complicated due to changes that impact other parts of the document, requiring updates to ensure consistency and comprehension.
Innovation Solution
A computer-implemented method defines data groups with associated rules to identify and process document elements, including numbers, dates, times, money, and business entities, allowing for user-editable rules and graphical indicators to facilitate document processing and searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hierarchical document structure is used to improve comprehension and cross-referencing, then document organization and understanding are improved, but document management complexity increases during creation and editing
Solution Approach 1:
The system automatically detects hierarchical structure elements (headers, paragraphs, lists) and generates the hierarchy without requiring manual user configuration. The document structure organizes itself based on predefined rules about element relationships, eliminating the need for users to manually manage hierarchical complexity while maintaining comprehension benefits
Solution Approach 2:
The system pre-defines data groups and association rules before document processing. These rules automatically identify and link hierarchical elements (such as connecting figures to their captions, or tables to their references) in advance, so that when editing occurs, the system can quickly determine which elements need updating without complex real-time analysis
2Productivity
If elements are added, moved, or modified in hierarchical document structure, then document content is updated, but other portions of the document require updates to maintain consistency
Solution Approach 1:
The system continuously monitors document structure elements and automatically detects when edits occur. When an element is added, moved, or modified, the system provides feedback by identifying all dependent elements that require corresponding updates, and automatically performs those updates to maintain consistency throughout the document hierarchy
Solution Approach 2:
The system pre-establishes association rules that define relationships between document elements (such as which figures reference which text, or which sections depend on which headings). These pre-defined relationships enable the system to quickly determine the scope of required updates when edits occur, eliminating the need for manual consistency checks
3Productivity
If automated processing is used to identify document elements, then editing efficiency is improved, but system complexity increases
Solution Approach 1:
The system divides document elements into predefined data groups (such as headers, paragraphs, lists, figures, tables) with specific characteristics. Each group has predefined association rules that define how elements within and between groups relate to each other. This segmentation allows automated processing to efficiently identify and manipulate elements without requiring complex general-purpose analysis
Solution Approach 2:
The system uses a universal framework of data groups and association rules that can apply to various types of documents and hierarchical structures. The same processing mechanisms work across different document formats and hierarchy levels, reducing the need for document-specific complex processing logic while maintaining high editing efficiency
Data Source
AI summary
A computer-implemented method and computing system are provided for defining a plurality of data groups. A set of rules may be associated with each of the data groups. The set of rules may define examples of items that should be included in each group. A document may be processed to identify elements within the document that adhere to a set of rules.