AI Document Classification Using Hierarchical Attention
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing document evaluation processes are subjective, leading to inconsistent criteria and reduced efficiency, as they rely heavily on human intervention without providing an objective basis for evaluation.
Innovation Solution
An artificial intelligence-based document classification apparatus and method utilizing a hierarchical attention network (HAN) and semantic analysis techniques to evaluate documents, providing an objective evaluation index and explainable basis for the evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human evaluators manually assess documents, then they can provide detailed evaluation, but the evaluation criteria become subjective and inconsistent
Solution Approach 1:
The patent replaces the mechanical system of human manual evaluation with an AI-based automated system that uses natural language processing and machine learning models to assess documents. This substitution eliminates human subjectivity while maintaining evaluation capability, directly resolving the contradiction between evaluation consistency and human intervention level.
Solution Approach 2:
The system enables self-service evaluation where the AI model independently performs document assessment without requiring human evaluators. The model automatically extracts features, applies classification criteria, and generates evaluation results, achieving both high consistency and minimal human intervention simultaneously.
2Productivity
If manual document evaluation is performed, then evaluators can consider contextual nuances, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent substitutes manual mechanical review processes with automated AI-based processing that can rapidly analyze documents. The system uses optical character recognition, natural language processing, and machine learning classification to evaluate documents instantly, dramatically increasing productivity while eliminating time-consuming manual review.
Solution Approach 2:
The system performs preliminary automated analysis and classification before any potential human review. By pre-processing documents through AI models that extract key features and determine categories in advance, the system prepares evaluation results ready for delivery, eliminating time loss entirely.
3Reliability
If AI technology is introduced for document evaluation, then objectivity can be improved, but the system complexity increases
Solution Approach 1:
The patent segments the complex AI evaluation system into distinct functional modules: document preprocessing module, feature extraction module, classification module, and result generation module. Each module handles a specific task independently, making the overall complex system manageable and maintainable while ensuring objective evaluation through coordinated operation of these segmented components.
Solution Approach 2:
The system introduces an intermediary layer of AI models and algorithms that mediate between the input documents and the evaluation output. This intermediary AI processing layer ensures objective, consistent, and reliable evaluation while the modular architecture keeps the complexity manageable through standardized interfaces and clear data flow between components.
Data Source
AI summary
The present disclosure in some embodiments provides an artificial intelligence or AI-based document classification apparatus and method for providing, based on a hierarchical attention network (HAN) and a semantic analysis technique, an evaluation of a document, and an explainable basis or supporting data for the evaluation, thereby generating an evaluation index for the document.