Cross-Column Relationship Detection via Image Representation

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Solution Overview

Problem

Current technologies face challenges in efficiently detecting relationships across database columns, leading to suboptimal data storage and retrieval efficiency.

Innovation Solution

The use of feature-based and deep-learning-based similarity models to generate augmented data columns, process image representations, and display related subsets through a cross-column relationship detection user interface, facilitating efficient cross-data-column relationship detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional methods are used to detect relationships across database columns, then the detection process is simple, but the detection accuracy and completeness are insufficient

Engineering Contradiction:

Improverelationship detection accuracyVSAvoiddetection system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces image representations as an intermediary medium between raw data columns and relationship detection algorithms. Data columns are transformed into visual image formats that capture spatial and structural patterns, enabling more accurate relationship detection through image processing techniques while maintaining system modularity

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces traditional mechanical or algorithmic data comparison methods with deep learning-based image recognition systems. By substituting conventional relationship detection mechanisms with neural network models trained on image data, the system achieves superior detection accuracy and completeness

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If data columns are analyzed individually without augmentation, then the processing is faster, but the relationship detection capability is limited

Engineering Contradiction:

Improvedata processing speedVSAvoidrelationship detection capability

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent performs preliminary data augmentation and image representation generation before the actual relationship detection process. By pre-processing data into enhanced visual formats that encode relational information, the system prepares data structures that enable more versatile and accurate relationship detection without significantly impacting overall processing throughput

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent transforms one-dimensional data column representations into two-dimensional image representations, adding a spatial dimension that encodes additional relational information. This dimensional transformation enables the detection of patterns and relationships that are not apparent in traditional linear data formats

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS11567976B2Detecting relationships across data columns

Publication Date: 2023.01.31 OPTUM TECH INC

AI summary

There is a need for more effective and efficient detection of cross-data-column relationships. This need can be addressed by, for example, techniques for detecting cross-data-column data relationships that utilize at least one of feature-based similarity models and deep-learning-based similarity models. The cross-data-column data relationships may be displayed to an end-user using a cross-column relationship detection user interface.