Unstructured Text Relationship Detection via Pattern Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Detecting relationships between entities in unstructured text within large document sets is laborious and inefficient, requiring manual effort and lacking scalable automated solutions.
Innovation Solution
A system and method utilizing text patterns with regular expressions and slots to identify entities and relationships, including preprocessing and pattern matching to automatically detect relationships in unstructured text documents, using a proper noun tagger, keyword identifier, and relationship detector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection of relationships is used, then accuracy can be maintained, but processing time and labor effort increase significantly
Solution Approach 1:
The patent replaces manual mechanical reading and analysis with automated computer-based pattern matching systems. The system uses text pattern templates and regular expressions to automatically detect relationships in documents, substituting human cognitive processing with computational algorithms that can process large volumes of text rapidly and consistently.
Solution Approach 2:
The system enables self-service relationship detection by allowing users to define custom text patterns and relationships without requiring complex programming. The pattern matching engine automatically processes documents using user-defined templates, making the system accessible to users with minimal technical expertise while maintaining high detection accuracy.
2Productivity
If automated pattern matching is implemented, then processing speed increases, but system complexity increases
Solution Approach 1:
The patent segments the relationship detection task into distinct modular components: text pattern definition, pattern matching engine, entity extraction, and relationship verification. Each component operates independently and can be optimized or modified without affecting the entire system, reducing overall complexity while maintaining high processing speed.
Solution Approach 2:
The system handles complexity by allowing flexible parameter changes in text pattern templates rather than requiring complex structural modifications. Users can adjust pattern parameters such as text expressions, slot positions, and matching criteria to adapt to different document types and relationship types, simplifying system configuration while maintaining high productivity.
3Measurement precision
If text pattern matching with multiple slots is used, then relationship detection precision improves, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining text patterns with slots and their expected positions before document processing. The system pre-compiles pattern templates with regular expressions and slot specifications, so that during actual processing, the engine only needs to match against pre-prepared templates rather than analyzing text structure in real-time, reducing processing time while maintaining high precision.
Data Source
AI summary
Disclosed are embodiments of a system and a method for detecting relationships described in unstructured text-based electronic documents. The system and method incorporate the use of an input file that contains one or more text patterns that represent particular relationships. The text patterns each include regular text expressions that describe the particular relationship and slots for the location of each entity in that relationship. Document(s) are selected by a user and scanned by a proper noun tagger that identifies and tags every occurrence of proper names within the document(s). Then, a pattern matcher scans the document(s) to match text patterns. If a text pattern is matched within a document a relationship detector extracts all pairs of proper names found in the slots for each matched text pattern. The output from the relationship detector includes the names for each entity in the relationship, the type of relationship, and the identity of the document and the location of the sentence describing the relationship in the document.