Numeric Expression Analysis for Domain Adaptation
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Solution Overview
Problem
Existing AI systems face challenges in generating natural and fluent numeric expressions, as they often provide excessive precision, and require specific domain designs to handle formatting and representation variations across different domains.
Innovation Solution
A method and system that ingest text corpora from target domains to infer rules for representing numeric quantities, automatically determining common and frequent numeric expressions, allowing for natural and expected formatting within each domain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AI systems use high precision numeric expressions, then measurement precision is improved, but naturalness and domain appropriateness deteriorate
Solution Approach 1:
The system dynamically adjusts numeric expression parameters (precision, format, representation) based on the target domain and context. By analyzing domain-specific text corpora, the system learns appropriate precision levels and formatting conventions for each domain, transforming rigid high-precision output into adaptive, context-appropriate numeric expressions that appear natural to domain experts.
2Adaptability or versatility
If AI systems manually program domain-specific formatting rules, then domain adaptability is improved, but device complexity and development time worsen
Solution Approach 1:
The system automatically learns and generates domain-specific numeric expression rules by analyzing text corpora from target domains. Instead of requiring manual programming of formatting conventions, the system self-tracts precision preferences, unit preferences, and representation patterns from domain-specific documents, enabling new domains to be supported without manual rule creation.
Solution Approach 2:
The system performs preliminary analysis of domain-specific text corpora to pre-learn formatting conventions and numeric expression patterns before actual numeric expression generation. By ingesting and analyzing domain documents in advance, the system builds domain-specific knowledge bases that guide subsequent numeric expression formatting, eliminating the need for manual rule programming at deployment time.
Data Source
AI summary
A method, computer program product and computer system are provided. A processor identifies a plurality of numeric expressions in a text corpus associated with a type of item. A processor generates a plurality of feature vectors corresponding to the identified plurality of numeric expressions. A processor identifies one or more common features of the plurality of feature vectors. A processor generates one or more rules for representing numeric quantities of the type of item based, at least in part, on the one or more common features of the plurality of feature vectors.