Document Segmentation Mapping for Accurate Content Retrieval
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional document processing techniques are inefficient and prone to errors due to the need for manual intervention, format conversion, and lack of automated methods for managing and analyzing diverse document collections, especially in industries requiring extensive information processing.
Innovation Solution
A computerized system that utilizes geographic information systems and natural language processing to manage document content by mapping documents into a coordinate system, allowing for automated segmentation, enrichment, and metadata generation, enabling flexible data access and manipulation based on physical geometry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual visual search and keyword search techniques are used to find areas of interest in documents, then search capability is provided, but the process is tedious and time-consuming when repeated across many documents from multiple sources
Solution Approach 1:
The patent replaces manual visual search and keyword search with an automated computer vision system that detects, segments, and indexes visual elements (charts, graphs, tables, images) directly from documents. The system automatically extracts visual information and creates searchable metadata, eliminating the need for human operators to manually search through multiple documents while maintaining comprehensive search capability across diverse document formats and sources.
Solution Approach 2:
The patent performs preliminary processing by automatically detecting, segmenting, and indexing visual elements before they are needed for search or analysis. The system pre-processes documents by extracting visual information and creating structured metadata representations, so that when search queries are later executed, the information is already organized and ready for rapid retrieval without requiring manual preparation or processing time.
2Reliability
If documents are converted to a common format by human transcription or copy/paste, then data consolidation is achieved, but the process is prone to errors, duplication, and requires human intervention
Solution Approach 1:
The patent replaces manual transcription and copy/paste operations with an automated computer vision and processing system that directly extracts visual elements and their associated data from source documents. The system automatically converts diverse document formats into a standardized internal representation without human intervention, eliminating transcription errors, duplication, and omissions while maintaining high data accuracy through direct digital extraction and structured metadata generation.
Solution Approach 2:
The patent creates accurate digital copies of visual elements and their metadata representations directly from source documents, preserving all information without manual transcription. The system generates precise replicated representations of charts, graphs, tables, and images as structured data objects that can be searched, filtered, and manipulated computationally, eliminating the errors and duplications inherent in manual copying processes.
3Measurement precision
If primitive keyword search techniques are used to find areas of interest, then search function is provided, but the accuracy is limited by guessing at the wording used inside documents
Solution Approach 1:
The patent segments documents into distinct visual elements (charts, graphs, tables, images) and their associated metadata, creating separate indexable units that can be precisely searched and retrieved. This segmentation allows the search system to accurately locate specific visual information without relying on keyword guessing, as each segmented element has structured metadata that directly describes its content, position, and characteristics, dramatically improving search accuracy while keeping the system architecture manageable through modular design.
Data Source
AI summary
Methods and systems are provided to manage documents and extract information from documents by defining segments in each document, each of which is assigned a location in a coordinate system defined over a collection of documents. Metadata is attached to each segment to describe the contents, position, and semantic meaning of material within the segment. A segmenting-specific query language can be used to query the segments and respond to requests for information contained in the documents.