Deconstructed Document Sections for Automated Report Generation
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Solution Overview
Problem
Current data management systems face inefficiencies in storing and processing large volumes of documents, leading to data duplication and high storage overhead, as they typically store entire documents rather than deconstructed sections, which limits effective automated report generation.
Innovation Solution
A system and method for generating report data structures by deconstructing documents into sections, determining attributes, and applying report generation rules to select and arrange relevant sections into a report template, minimizing storage needs and enabling dynamic report creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If entire documents are stored in data management systems, then complete information is preserved, but data storage overhead increases and data duplication occurs
Solution Approach 1:
The system segments documents into smaller meaningful sections (headers, paragraphs, lists, tables, images) and stores only the relevant sections needed for report generation. This segmentation allows the system to preserve necessary information while reducing storage overhead by excluding irrelevant portions of documents.
Solution Approach 2:
The system extracts and stores only the essential document sections that are relevant to specific report types, rather than storing entire documents. This extraction process removes redundant information and reduces data duplication while maintaining the completeness of information needed for report generation.
2Adaptability or versatility
If entire documents are stored, then all possible report data is available, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing by deconstructing documents into structured sections and pre-tagging them with metadata during the ingestion phase. This preliminary action enables faster retrieval and assembly of report data later, reducing processing time while maintaining adaptability to different report requirements.
Solution Approach 2:
By segmenting documents into reusable sections with associated metadata, the system enables efficient retrieval and recombination of document parts for different report types. This segmentation reduces processing time by avoiding the need to parse entire documents during report generation.
3Quantity of substance
If deconstructed document sections are stored instead of entire documents, then storage overhead is reduced, but system complexity increases
Solution Approach 1:
The system employs a universal document section model that can represent various document elements (headers, paragraphs, lists, tables, images) using a common structure. This multi-functional approach reduces system complexity by providing a standardized way to handle diverse document types while maintaining storage efficiency.
Solution Approach 2:
The system uses metadata parameters to describe document sections, allowing flexible representation and retrieval without complex structural changes. By changing from storing complete document structures to storing parameterized section descriptions, the system achieves storage efficiency while managing complexity through standardized parameter handling.
4Extent of automation
If deconstructed document sections with attributes are stored, then automated report generation is enabled, but data processing complexity increases
Solution Approach 1:
The system enables automated report generation by equipping document sections with self-descriptive metadata and attributes that allow the report generation engine to automatically identify, select, and assemble relevant sections without complex manual processing. This self-service approach reduces processing complexity by allowing data to describe itself.
Solution Approach 2:
The system introduces an intermediary layer of metadata and attributes that bridges raw document sections and report generation requirements. This intermediary structure simplifies automation by providing a standardized interface between document content and report templates, reducing the complexity of direct processing.
Data Source
AI summary
Methods, systems, apparatus, and computer programs for generating a report data structure using deconstructed document sections. In one aspect, the method includes actions of obtaining a plurality of deconstructed document sections, determining, for each deconstructed document section, one or more deconstructed document section attributes based on natural language text of the one or more respective deconstructed document sections, identifying one or more report generation rules defining data directed dynamic conditional statements that include operations for generating a report using the plurality of deconstructed document sections, determining, by applying the one or more identified rules defining data directed dynamic conditional statements to the deconstructed document sections, a subset of the plurality of deconstructed document sections that are to be incorporated into a report, and generating a report that includes the subset of the plurality of deconstructed document sections.