Automated Fact Extraction Using Title and Contextual Patterns
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The vast volume of web-based documents makes it impractical for human editors to efficiently identify and extract objects and facts, necessitating an automated solution for mass fact extraction.
Innovation Solution
A system and method that select a source object and document, identify title and contextual patterns, and associate objects with identified facts by applying these patterns to a set of documents, creating or merging objects within a fact repository.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human editors manually identify and extract objects and facts from documents, then extraction accuracy and quality are improved, but productivity and scalability are worsened due to the vast volume of documents
Solution Approach 1:
The patent replaces the manual mechanical process of human editors extracting facts with an automated computational system. The system uses pattern recognition algorithms to automatically identify objects and facts from documents, substituting human cognitive processing with computer-based pattern matching and extraction mechanisms.
Solution Approach 2:
The system enables self-service fact extraction by automatically learning and applying patterns from source documents without requiring human intervention for each extraction task. The pattern recognition system autonomously processes documents, identifies objects and facts, and populates the fact repository without manual editing.
2Productivity
If automated pattern recognition is used to extract facts from documents, then productivity and scalability are improved, but measurement precision and extraction accuracy are worsened
Solution Approach 1:
The system performs preliminary pattern learning by analyzing source documents to identify title patterns and contextual patterns before extracting facts from target documents. This preliminary action of pattern recognition and classification prepares the system to accurately extract facts from new documents by matching them against learned patterns.
Solution Approach 2:
The system incorporates feedback mechanisms where extracted facts are validated and used to refine pattern recognition. The fact repository stores extracted information that can be referenced to improve future extractions, creating a feedback loop that enhances accuracy over time as the system processes more documents.
3Productivity
If the system processes a large set of documents to improve coverage, then productivity is improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent segments the document processing task into distinct phases: pattern learning phase (analyzing source documents to identify title and contextual patterns) and fact extraction phase (applying patterns to target documents). This segmentation allows the system to handle large volumes of documents by reusing learned patterns rather than reanalyzing all documents from scratch.
Solution Approach 2:
The pattern recognition system serves multiple functions: it identifies title patterns from document headings, extracts contextual patterns from document content, classifies documents into categories, and guides fact extraction. This multi-functionality reduces overall system complexity by consolidating multiple processing tasks into a unified pattern-based framework.
Data Source
AI summary
A system, method, and computer program product for learning objects and facts from documents. A source object and a source document are selected and a title pattern and a contextual pattern are identified based on the source object and the source document. A set of documents matching the title pattern and the contextual pattern are selected. For each document in the selected set, a name and one or more facts are identified by applying the title pattern and the contextual pattern to the document. Objects are identified or created based on the identified names and associated with the identified facts.