Active Ontology Framework for Intelligent Assistant Development
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Solution Overview
Problem
The development of intelligent automated assistants is complex and inefficient due to the need for multiple skilled individuals with expertise in various programming languages and artificial intelligence methods, making it difficult for a lone software developer to build such systems.
Innovation Solution
The use of active ontologies as a unified framework that integrates multiple system-building capabilities, allowing for the creation of execution environments that model domains and process inputs to produce actions, enabling efficient development of intelligent automated assistants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional development processes are used for building intelligent automated assistants, then the system can achieve high functionality with multiple capabilities, but the development complexity and time requirements increase significantly
Solution Approach 1:
The system segments the complex development process into distinct modular components including service-oriented architecture layers, active ontology modules, and standardized interfaces. This allows different functional capabilities (natural language recognition, multimodal input, service coordination) to be developed and integrated as separate modules, reducing overall development complexity while maintaining high system functionality
Solution Approach 2:
The patent introduces an intermediary framework consisting of active ontologies and service-oriented architecture that mediates between various software components and the final intelligent assistant system. This intermediary layer standardizes interactions between components, simplifying the integration process and reducing development complexity while enabling versatile system functionality
2Adaptability or versatility
If multiple skilled individuals with different expertise are involved in development, then the system achieves high functionality, but the manpower requirements and development costs increase
Solution Approach 1:
The service-oriented architecture and active ontology framework provide universal, multi-functional capabilities that can be reused across different intelligent assistant applications. Natural language recognition, multimodal input processing, and service coordination mechanisms are implemented as reusable components, allowing a single developer to access diverse functionalities without requiring multiple specialized experts
Solution Approach 2:
The system enables self-service development through standardized interfaces and automated service coordination mechanisms. The active ontology framework automatically manages service registration, discovery, and integration, reducing the need for manual coordination between multiple developers and enabling a single developer to build complex functional systems independently
3Adaptability or versatility
If comprehensive software components are integrated, then the intelligent assistant achieves high adaptability, but the integration process becomes inefficient and time-consuming
Solution Approach 1:
The patent implements preliminary action by pre-defining service-oriented architecture frameworks, active ontology structures, and standardized integration interfaces before actual system development. These pre-established templates and protocols enable rapid integration of software components without requiring time-consuming custom integration work, thus achieving high capability integration efficiency
Data Source
AI summary
A method and apparatus are provided for building an intelligent automated assistant. Embodiments of the present invention rely on the concept of “active ontologies” (e.g., execution environments constructed in an ontology-like manner) to build and run applications for use by intelligent automated assistants. In one specific embodiment, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontology includes at least one active processing element that models a domain. At least one of the remote services is then registered for use in the domain.