Graphical Knowledge Engineering Editor for Non-Technical Users
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Solution Overview
Problem
The technical complexity of existing knowledge engineering systems has limited their adoption beyond technical experts, making it difficult for non-technical subject matter experts to codify and use knowledge-based systems effectively.
Innovation Solution
A graphical user interface-based system for knowledge engineering that allows for the creation, editing, and maintenance of knowledge-based systems without requiring external tools, enabling a modal page metaphor for navigation, inline help, and conditional processing, making it accessible and portable across various platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional knowledge engineering systems are used, then knowledge modeling capability is achieved, but device complexity increases making it inaccessible to non-technical users
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates between user-friendly natural language inputs and formal knowledge engineering representations. This mediator layer allows non-technical users to interact with complex knowledge systems through simple language without needing to understand the underlying complexity, effectively resolving the contradiction between ease of operation and device complexity.
Solution Approach 2:
The patent replaces traditional mechanical/manual knowledge engineering processes with automated natural language processing and machine learning systems. Instead of requiring users to manually construct complex knowledge models, the system automatically generates and maintains knowledge representations through language processing, significantly reducing the perceived complexity for end users.
2Measurement precision
If manual knowledge codification is used, then knowledge accuracy is improved, but loss of time increases due to the lengthy development process
Solution Approach 1:
The patent implements preliminary action by pre-training language models on extensive knowledge corpora before actual knowledge engineering tasks. This pre-processing establishes foundational understanding and patterns that enable rapid, accurate knowledge codification during actual use, eliminating the need for time-consuming manual knowledge construction while maintaining high accuracy through the pre-established linguistic and conceptual frameworks.
Solution Approach 2:
The patent uses copying by replicating human expert knowledge patterns through natural language processing. Instead of manually codifying each knowledge element, the system analyzes and copies the structure, reasoning patterns, and knowledge relationships from existing expert systems and knowledge bases, rapidly reproducing accurate knowledge representations without repeating the original time-intensive development process.
3Ease of manufacture
If technical expertise is required for knowledge engineering, then manufacturing precision is maintained, but ease of manufacture decreases for non-technical SMEs
Solution Approach 1:
The patent implements self-service by enabling knowledge systems to automatically generate, validate, and maintain their own knowledge representations through natural language processing. The system performs self-validation, consistency checking, and quality assurance tasks that previously required technical expertise, allowing non-technical users to create precise knowledge models independently without needing external expert intervention.
Solution Approach 2:
The patent changes the fundamental parameters of knowledge engineering from technical code-based representations to natural language-based representations. This parameter transformation allows the system to maintain precision through linguistic structure and semantics while dramatically improving ease of manufacture, as users can work with familiar language rather than requiring specialized technical training in knowledge engineering formalisms.
Data Source
AI summary
A system and method is disclosed for knowledge engineering using a computerized graphical editor to manage and create knowledge-based systems containing a navigable graph of modal pages with conditional content and user interface knowledge. The invention enables the entire knowledge engineering workflow to be performed within a non-technical graphical environment and without requiring a computer programming or mathematical background. Further, the presentation of knowledge as modal pages allows for simple ontological discovery and end-user player operation. Once editing is complete, the method allows for the set of pages, variables, and settings of which the knowledge-based system is composed to be exported into an independently executable knowledge-based system player containing an embedded inference engine.