OCR Citation Mapping for Policy-Based Document Classification

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Solution Overview

Problem

Companies in highly-regulated industries face challenges in efficiently identifying and accessing relevant regulatory documents due to the dense and large volume of information, leading to manual and error-prone processes for tracking regulatory changes.

Innovation Solution

A system and method for automatically scraping, processing, and highlighting relevant regulatory documents using optical character recognition (OCR) and computer vision to identify regulatory citations, and establishing relationships between citations, requirements, and mandates, enabling rapid access and navigation through enforcement documents.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual tracking of regulatory documents is performed, then identification accuracy can be maintained through human judgment, but time consumption and labor costs increase significantly

Engineering Contradiction:

Improveidentification accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the mechanical human review process with an automated computer vision system that uses optical character recognition (OCR) and image processing algorithms to detect, extract, and classify regulatory citations from documents. This substitution maintains high identification accuracy while dramatically reducing time consumption and labor requirements.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the regulatory document processing system to automatically perform citation identification and extraction without requiring manual human intervention. The automated system serves itself by processing documents through configured rules and algorithms, eliminating the need for continuous human labor while maintaining consistent accuracy.

Inventive Principle:

Principle #25Self-service

2Reliability

If comprehensive regulatory documents are reviewed to ensure complete coverage, then identification completeness improves, but system complexity and processing difficulty increase

Engineering Contradiction:

Improveidentification completenessVSAvoidprocessing difficulty

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies segmentation by breaking down the complex task of regulatory document review into distinct processing stages: document ingestion, OCR text extraction, citation pattern recognition, classification, and result compilation. This modular approach ensures complete coverage of all regulatory citations while managing system complexity through structured, step-by-step processing.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system manages complexity by dynamically adjusting processing parameters such as citation detection sensitivity thresholds, classification rules, and extraction criteria based on the specific document type and regulatory context. This allows the system to maintain high identification completeness while adapting to varying document complexities without requiring overly complex fixed processing logic.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If automated processing is implemented to reduce manual effort, then processing speed increases, but risk of errors and false positives increases

Engineering Contradiction:

Improveprocessing speedVSAvoiderror rate

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent implements feedback mechanisms where the automated processing system continuously refines its citation detection and classification based on results from processed documents. The system learns from identified patterns and adjusts its processing algorithms to reduce false positives and errors, thereby maintaining high processing speed while improving reliability over time through iterative optimization.

Inventive Principle:

Principle #23Feedback

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Facilitates quick and accurate identification and presentation of relevant regulatory documents, reducing manual effort and errors, and allowing businesses to respond effectively to potential regulatory violations.

Implementation Method 1

using optical character recognition (OCR) and computer vision to identify regulatory citations

Methodology Applied

Scientific EffectOptical character recognition (OCR):

Data Source

PatentUS12456086B2Citation and policy based document classification

Publication Date: 2025.10.28 CAPITAL ONE SERVICES LLC

AI summary

Disclosed herein are system, method, and computer program product embodiments for rapid identification and access to relevant regulatory documents. A data model relating regulatory mandates and requirements to citations appearing within an enforcement document is used to rapidly access specific citations within an enforcement document. In the case of image-based enforcement documents, the originality of these documents is preserved while allowing a user to see where the relevant citations appear in the document images. The relevant citations are further compared to business policies to identify potential impacts of regulatory mandates and requirements.