Assertional Simulation for Multi-Ontology Decision Modeling

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Solution Overview

Problem

Current systems for decision-making in business and analytics fail to effectively handle alternative points of view by not facilitating the presentation of various potential structures or organizations, and existing simulation systems do not readily enable the handling of such perspectives.

Innovation Solution

A system for decision support is developed that includes a reference data set configured to omit structural constraints from diverse data sources, allowing for the de-referencing of data elements and the creation of a flat data file that represents both ontology-derived and structure-derived constraints, enabling the recombinant access and mediation of data across different ontologies and structures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If data is organized according to source-specific ontologies and structures, then data integrity and meaning are preserved, but adaptability to alternative points of view and recombinant access are reduced

Engineering Contradiction:

Improveadaptability to alternative points of viewVSAvoidloss of ontology-derived constraints

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The patent segments data into two distinct layers: a flat reference data set containing ontology-derived constraints and semantic meanings, and structure-specific data layers containing source-specific organizational constraints. This segmentation allows the reference data set to serve multiple ontologies and structures simultaneously, improving adaptability while preserving information in separate layers.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extracts ontology-derived constraints and semantic meanings from source-specific data structures to create a standalone reference data set. This extraction separates the essential semantic content from source-specific structural constraints, enabling the reference data to be reused across different ontologies and structures without losing critical information.

Inventive Principle:

Principle #2Taking out (Extraction)

2Adaptability or versatility

If a flat data structure is used to enable recombinant access, then adaptability and versatility improve, but the ability to represent structured relationships and constraints deteriorates

Engineering Contradiction:

Improverecombinant access capabilityVSAvoidcomplexity of representing structure

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary layer consisting of ontology labels and metadata that mediates between the flat reference data set and structure-specific requirements. These intermediaries encode structural relationships and constraints in a way that can be interpreted when data is accessed according to specific ontologies, allowing the flat structure to represent complex relationships without inherent complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent changes the parameter representation by storing ontology labels and semantic descriptors as data elements in the flat reference data set. These parameters can be dynamically interpreted and filtered according to different ontology requirements, allowing the same flat structure to serve multiple structural needs without increasing inherent complexity.

Inventive Principle:

Principle #35Parameter changes

3Ease of operation

If multiple ontologies are integrated into a unified structure, then ease of operation improves, but the complexity of managing diverse constraints increases

Engineering Contradiction:

Improveease of data accessVSAvoidcomplexity of constraint management

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent creates a universal reference data set that serves multiple ontologies and structures simultaneously. The reference data set is designed to be ontology-agnostic, containing core semantic information that can be accessed and interpreted according to any number of different ontologies without requiring separate data structures for each, thereby improving ease of operation while avoiding the complexity of managing multiple unified structures.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11361228B2Methods and systems of assertional simulation

Publication Date: 2022.06.14 GO LOGIC DECISION TIME LLC

AI summary

Managing looped, iterative and recursive operations through applying a parameterized instance of an assertion-model apportionment-sub-model pair to a reference data model to produce a parameterized outcome model. Based on a degree of convergence of the parameterized outcome model toward a target parameterized instance of the assertion-model apportionment-sub-model pair, assembling and parameterizing a next assertion-model and a next apportionment-sub-model pair. Repeating these steps until an instance of a parameterized outcome model meets a preconfigured degree of convergence toward a corresponding target parameterized instance of the assertion-model apportionment-sub-model pair.