Unicode Matching via Stroke and Radical Distance
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Solution Overview
Problem
Current systems are inefficient in comparing and merging data objects with Unicode strings that are not exact matches, particularly in languages like Japanese and Chinese, due to the large number of Unicode code points and lack of methods to utilize characteristics such as strokes, radicals, and input method editor associations.
Innovation Solution
A system and method that characterizes Unicode characters by stroke count, radicals, geometry, phonemes, and input method editor associations to calculate a 'distance' between code points, allowing for the comparison and merging of similar data objects with minor differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If Unicode code points are used to represent text in languages like Japanese and Chinese, then the ability to represent diverse characters and languages is improved, but the complexity of comparing and matching strings increases due to the large number of code points
Solution Approach 1:
The patent segments the Unicode code point into multiple characteristics: stroke count, radical components, phonetic information, and input method editor associations. By dividing the complex code point into these discrete features, the system can compare strings more efficiently without needing to process the entire Unicode value, thus reducing computational complexity while maintaining language representation capability.
Solution Approach 2:
The patent introduces an intermediary layer of characteristics between the Unicode code point and the comparison operation. Instead of directly comparing code points, the system compares derived features (stroke count, radicals, phonemes) that serve as mediators, making the comparison process more manageable and efficient for large character sets.
2Ease of operation
If traditional exact matching methods are used for Unicode strings, then the simplicity of the comparison process is maintained, but the ability to identify similar but not exact matches is lost
Solution Approach 1:
The patent segments the string comparison into multiple independent characteristic comparisons (stroke count, radical matching, phonetic similarity). This allows the system to maintain simple comparison operations for each characteristic while achieving reliable overall matching by aggregating results from multiple features, thus identifying duplicates that exact matching would miss.
Solution Approach 2:
The patent changes the comparison parameters from binary exact match to multi-dimensional similarity measurement. By transforming the comparison into a parameter-based similarity assessment across multiple characteristics, the system can reliably identify near-duplicates while maintaining operational simplicity through systematic evaluation of each parameter.
3Measurement precision
If characteristics such as stroke count and radicals are used to compare Unicode characters, then the accuracy of identifying similar strings is improved, but the computational requirements and system complexity increase
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing the characteristics (stroke count, radicals, phonemes) for each Unicode code point during data ingestion or indexing. This preliminary characterization allows the actual comparison operation to simply retrieve and compare pre-computed features rather than analyzing characters in real-time, thus improving measurement precision while limiting the complexity to data preparation rather than execution time.
Solution Approach 2:
The patent creates a simplified representation (copy) of the Unicode code point's essential characteristics for comparison purposes. Instead of working with the full complexity of the code point, the system uses a simplified characteristic model that captures the necessary information for similarity measurement, reducing computational requirements while maintaining measurement accuracy.
Data Source
AI summary
System and method for performing Unicode matching for comparing and merging similar data objects having Unicode strings that are equivalent yet not exact matches. Unicode characters are characterized by number of strokes, stroke order, radicals, geometry, phonemes in association with input method editor and keyboard characteristics such as location of a character on an IME or keyboard (or number of GUI interface interactions used in entering the character, e.g., via tapping where “a” on a mobile device keyboard takes 1 tap of a key, “b” takes 2 taps). These characteristics associated with code points and IME's/keyboards are utilized to create subdomains for matching and determining “distance” to other Unicode code points (e.g., number of keyboard keys away). Allows for determining whether close, yet incorrect data entry may have taken place. Enables merging of duplicate data objects into master data object where minor differences or spelling errors introduce actually represent duplicate data.