Date Ambiguity Resolution via Confidence-Based Format Merging
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Solution Overview
Problem
Dates extracted from conflicting or unreliable sources often contain ambiguities and errors due to various formats and typographical errors, leading to a lack of confidence and accuracy in date values.
Innovation Solution
A method that involves obtaining and analyzing text strings to determine if they conform to specific date formats, assigning confidence values based on specificity, and merging date formats with the highest confidence values to obtain a reliable date value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If dates are extracted from multiple sources with different formats, then the quantity of date information increases, but the accuracy and reliability of the extracted dates deteriorates due to ambiguities and errors
Solution Approach 1:
The patent segments the date extraction and validation process into distinct modules: extraction, format detection, confidence scoring, and merging. Each module handles a specific aspect of date processing independently, allowing the system to process multiple date formats while maintaining reliability through structured validation at each stage.
Solution Approach 2:
The patent implements feedback mechanisms through confidence scoring, where the system evaluates the reliability of extracted dates and uses this information to guide subsequent processing. Dates with lower confidence scores can be re-examined or discarded, while high-confidence dates are prioritized in the merging process, creating a feedback loop that improves overall reliability.
2Quantity of substance
If date formats from multiple sources are merged, then the completeness of date information improves, but the complexity of processing and resolving ambiguities increases
Solution Approach 1:
The patent changes the parameter of date representation by converting all extracted dates into a standardized internal format before merging. This parameter transformation simplifies the merging process by eliminating the need to handle multiple date formats simultaneously, reducing processing complexity while maintaining completeness.
Solution Approach 2:
The patent introduces an intermediary confidence scoring mechanism that mediates between the raw extracted dates and the final merged result. This intermediary layer processes and evaluates date formats before merging, simplifying the overall process by handling format variations and ambiguities in a dedicated intermediate step.
3Measurement precision
If confidence values are assigned based on specificity, then the accuracy of date determination improves, but the time required for analysis increases
Solution Approach 1:
The patent applies partial action by assigning confidence values only to the most relevant date format possibilities rather than exhaustively analyzing all potential interpretations. This selective approach maintains sufficient accuracy for practical purposes while significantly reducing the time required for analysis by avoiding over-processing of unlikely date format interpretations.
Data Source
AI summary
A system and method for resolving ambiguities in date values associated with an attribute in a memory of the computer system. If a first text string conforms to one or more date formats, a confidence value is assigned for each of the date formats for the first text string based on the amount of specificity with which the first text string conforms to each date format. Similarly, if a second text string conforms to one or more date formats, a confidence value is assigned for each of the date formats for the second text string based on the amount of specificity with which the second text string conforms to each date format. The date format with the highest confidence value for the first text string and the date format with the highest confidence value for the second text string are merged to obtain a date value for the attribute.