Protocol-Based Data Classification for HR Migration Error Correction

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Solution Overview

Problem

Computing engines face challenges in accurately processing matrices from different computing platforms due to data inconsistencies and errors, leading to crashes, increased latency, and wastage of computing resources during data migration between HR platforms.

Innovation Solution

A platform that uses protocols and algorithms to identify and correct placeholders in data structures by predicting values for placeholders, transforming data structures to a standardized format, and removing duplicated data, thereby reducing errors and overhead.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual classification of data is performed for each HR platform, then data accuracy can be improved, but significant overhead of computing system and wasted computing resources occur

Engineering Contradiction:

Improvedata accuracyVSAvoidcomputing resources

Core Design Contradiction:

Measurement precisionVSLoss of energy

Solution Approach 1:

The system performs self-service by automatically classifying data using machine learning models and algorithms, eliminating the need for manual classification. The platform autonomously identifies data types, applies appropriate classification rules, and migrates data between HR platforms without human intervention, thereby improving data accuracy while reducing computing resource overhead.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical classification processes with automated electronic systems. Machine learning models and classification algorithms substitute human operators, enabling rapid and accurate data classification without the time and resource consumption associated with manual methods.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Stability of the object's composition

If data migration is performed frequently between HR platforms, then data consistency can be improved, but excessive utilization of computer resources, memory, and network bandwidth occurs

Engineering Contradiction:

Improvedata consistencyVSAvoidcomputer resources

Core Design Contradiction:

Stability of the object's compositionVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary actions by pre-classifying and validating data before migration occurs. The platform prepares data structures, applies classification rules in advance, and optimizes migration paths, which reduces the need for frequent corrective migrations and decreases overall resource utilization while maintaining data consistency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent utilizes parameter changes by dynamically adjusting migration frequencies and data classification parameters based on system load, data criticality, and resource availability. This allows the system to maintain data consistency through selective migrations rather than frequent continuous migrations, optimizing resource usage.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If erroneous data structures are processed by computing engine, then data processing can be performed, but computing engine crashes or errors are introduced

Engineering Contradiction:

Improvedata processingVSAvoidsystem stability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system applies beforehand cushioning by implementing validation rules, error detection mechanisms, and classification verification before data structures are processed by the computing engine. The platform identifies and corrects potential errors in advance, preventing crashes and ensuring system stability while maintaining productive data processing.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

4Loss of energy

If data classification is performed automatically using protocols, then computing resource wastage is reduced, but processing time may increase due to protocol execution

Engineering Contradiction:

Improvecomputing resource wastageVSAvoidprocessing time

Core Design Contradiction:

Loss of energyVSLoss of time

Solution Approach 1:

The patent implements periodic action by executing data classification protocols at optimized intervals rather than continuously. The system performs classification operations periodically based on data change events, migration triggers, or scheduled tasks, reducing overall processing time while maintaining resource efficiency through targeted protocol execution.

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS20260064644A1Automatic data classification using a protocol

Publication Date: 2026.03.05 ADP INC

AI summary

This technology can provide a platform using one or more protocols to migrate and correct erroneous data. The platform can receive a data structure that includes a plurality of placeholders in accordance with payroll of an entity. The platform can obtain, identify, retrieve, or otherwise receive a template that includes references codes to classify each placeholder within the data structure. Upon classifying each placeholder, the platform can execute a protocol to perform a reverse search and fill the placeholders of the original data structure. For example, the platform can predict values for the placeholders and fill the predicted values for the placeholders’ using results of the reverse search associated with the predicted values. The platform can fill the placeholders with actual values to correct the erroneous data structure and transmit the data structure to a migration system.