Process Model Auto-Update via External Data NLP

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Solution Overview

Problem

Existing computer models of real-world processes lack the ability to automatically update and adapt to external, real-time data sources, leading to inefficiencies and inconsistencies as external factors change rapidly.

Innovation Solution

A computer system that utilizes natural language processing to analyze external data sources, determine semantic similarities with existing process models, and automatically update the models by adding or removing steps based on categorized text data, allowing for real-time adaptation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If computer models of real-world processes are manually maintained without automatic updating, then the models remain stable and consistent, but they become outdated and inconsistent with external real-time data changes

Engineering Contradiction:

Improveconsistency of process modelVSAvoidability to adapt to external changes

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system continuously monitors external data sources and automatically compares them against the process model to detect changes. This feedback loop ensures the model remains synchronized with external realities by triggering automatic updates when discrepancies are detected, resolving the contradiction between maintaining consistency and adapting to changes.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The process model automatically updates itself by retrieving external data, analyzing changes through NLP, and modifying its own structure without manual intervention. This self-service capability allows the model to maintain both consistency through automated validation and adaptability through autonomous updates to external changes.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If manual updates are performed to keep process models aligned with external changes, then the models remain relevant, but significant manual effort and time are required

Engineering Contradiction:

Improverelevance of process modelVSAvoidmanual update time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs complete automatic updating by autonomously retrieving external data, analyzing it through natural language processing, identifying changes, and modifying the process model without human intervention. This eliminates manual update time while maintaining model relevance through continuous automated synchronization with external data sources.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The manual mechanical process of updating models is replaced with an automated computational system that uses natural language processing and algorithmic change detection. This substitution eliminates the need for manual effort and time while maintaining or improving the relevance of process models through faster, continuous automated updates.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Extent of automation

If natural language processing is used to automatically analyze external data and update process models, then manual intervention is reduced, but system complexity increases

Engineering Contradiction:

Improveautomatic model updatingVSAvoidsystem complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The system introduces an intermediary natural language processing layer that automatically translates external data into structured change detections and model updates. This intermediary handles the complexity of NLP and change analysis, allowing the core process model to remain simple while achieving high automation through the mediating NLP system that manages the complexity of interpreting external data.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Adaptability or versatility

If process models are frequently updated to reflect external changes, then they remain current, but the risk of introducing errors increases

Engineering Contradiction:

Improvecurrentness of process modelVSAvoidaccuracy of process model

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system uses feedback mechanisms to validate changes before applying them to the process model. External data is continuously monitored and compared against the current model state, with changes only applied after verification through NLP analysis and change detection algorithms. This feedback loop maintains currentness while ensuring accuracy by preventing unvalidated changes.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary analysis and validation of external data through natural language processing before applying updates to the process model. Changes are detected and verified in advance through automated comparison and NLP analysis, ensuring that only accurate, validated changes are implemented. This preliminary action maintains model currentness while protecting against errors through pre-validation.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11321531B2Systems and methods of updating computer modeled processes based on real time external data

Publication Date: 2022.05.03 SAG ARIS GMBH

AI summary

A system for automatically updating a process model is provided. The system uses semantic similarities between externally sourced textual data and textual descriptions contained in the process model to classify words in the externally sourced textual data into one of multiple possible actionable categories. The textual data is then parsed for dependent words that are used to automatically update to an existing process model.