Digital Standards Similarity Search Using Unified Attribute Types

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Solution Overview

Problem

Existing methods for searching and identifying similar objects within digital standards are inefficient and time-consuming, especially when dealing with complex and extensive industry standards, as they often require one-to-one comparisons of attributes with potential inaccuracies due to differing formats.

Innovation Solution

A system and method for performing document attribute comparisons by converting attributes to a defined data type for similarity comparisons, allowing for faster and accurate identification of similar objects across digital standards, even when attributes have different data types.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If one-to-one comparison of attributes is performed across digital standards, then similarity identification can be achieved, but the process becomes inefficient and time-consuming

Engineering Contradiction:

Improvesimilarity identification accuracyVSAvoidsearch time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent transforms attribute data by converting different data types (string, integer, float, boolean) into a unified numerical representation. This parameter transformation enables efficient computational comparison while maintaining accuracy, resolving the contradiction between precise similarity identification and search efficiency

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the manual one-to-one attribute comparison mechanism with an automated computational system that uses data type substitution and algorithmic processing. This substitution eliminates time-consuming manual comparisons while maintaining identification accuracy through systematic data transformation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If attributes with different data types are compared directly, then comparison can be performed, but inaccuracies occur due to format differences

Engineering Contradiction:

Improvecomparison speedVSAvoidcomparison accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent applies parameter transformation by converting all attribute data types into a common numerical format. This allows attributes of different types (string, integer, float, boolean) to be compared accurately on the same scale, eliminating format-related inaccuracies while enabling fast computational processing

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent creates a universal comparison framework that handles multiple data types through a single substitution mechanism. By defining a unified data type representation that can accommodate various original formats, the system achieves both high-speed processing and accurate comparison across diverse attribute types

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250342160A1Similarity searching across digital standards

Publication Date: 2025.11.06 SAE INT

AI summary

One embodiment provides a method for identifying similar objects by performing document attribute comparisons, the method including: providing a digital standard system that includes a user interface and a data store of digital standards; receiving a request for a similarity comparison; performing the similarity comparison; generating a document similarity score for each of the digital standards within a group of digital standards; and displaying at least one of the digital standards from the group based upon the document similarity score. Other aspects are described and claimed.