Knowledge Abstraction Layer for Unified Logic Storage

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Solution Overview

Problem

Existing computer programs struggle to effectively store and utilize both factual and logical knowledge due to their segregation, leading to inflexible and redundant systems with elevated costs and decreased reliability, as logical knowledge is encoded in algorithms and not readily available for inference.

Innovation Solution

A Knowledge Abstraction Layer system that combines factual and logical knowledge using a Functional Logic Knowledge (FLK) repository, enabling querying and inference through a processor-configured memory system with a hierarchical taxonomy naming convention, allowing for the storage and retrieval of complete domain knowledge.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If logical knowledge is encoded as algorithms in program code, then the program can execute logical operations, but the logical knowledge becomes sequestered and inflexible with limited scope and reusability

Engineering Contradiction:

Improveexecution reliabilityVSAvoidknowledge flexibility

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent extracts logical knowledge from program code and places it into a separate knowledge base that can be independently stored, retrieved, and applied. This extraction allows logical knowledge to be reused across multiple programs without being sequestered in algorithmic form, thereby improving both execution reliability and knowledge flexibility simultaneously

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent introduces a knowledge base as an intermediary layer between data storage and program execution. This intermediary stores logical knowledge in a structured format that can be queried and applied by multiple programs, serving as a mediator that decouples the rigidity of coded algorithms from the need for reliable logical operations

Inventive Principle:

Principle #24Intermediary (Mediator)

2Speed

If factual knowledge and logical knowledge are stored separately, then data retrieval is efficient, but the full scope of knowledge cannot be curated together or evaluated as a whole

Engineering Contradiction:

Improvedata retrieval speedVSAvoidknowledge completeness

Core Design Contradiction:

SpeedVSLoss of information

Solution Approach 1:

The patent merges factual knowledge and logical knowledge into a unified knowledge base structure where both types of knowledge coexist and can be queried together. This combination allows the system to evaluate the full scope of knowledge as a whole while maintaining efficient retrieval through structured indexing and organization

Inventive Principle:

Principle #5Merging (Combining)

3Ease of manufacture

If domain knowledge is segmented and stored in separate systems, then each system can specialize, but the knowledge becomes redundant and inconsistent with elevated system costs

Engineering Contradiction:

Improvesystem specializationVSAvoidknowledge consistency

Core Design Contradiction:

Ease of manufactureVSReliability

Solution Approach 1:

The patent creates a universal knowledge base that can serve multiple specialized systems simultaneously. This multi-functional repository allows different systems to access and apply the same curated domain knowledge, eliminating redundancy and ensuring consistency across specialized applications while maintaining the benefits of system specialization

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11468340B2Method and system for using data storage technology as a repository of functional logic knowledge for use in a knowledge abstraction layer subsystem

Publication Date: 2022.10.11 GENESEE VALLEY INNOVATIONS LLC

AI summary

This disclosure provides a knowledge base system and method for curating both factual and logical knowledge while using a common data storage repository. According to an exemplary embodiment, a knowledge base stores complied Boolean information which represents factual knowledge and logic for interpreting the factual knowledge. Combining the knowledge base, i.e., functional logic knowledge (FLK) repository, with a logic evaluator creates a knowledge abstraction layer.