Natural Language Interface Ontology Generation
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Solution Overview
Problem
Generating a user interface for a repository requires substantial effort and expert knowledge, making it complex and inaccessible to non-technical users, especially when interpreting user-entered natural-language statements.
Innovation Solution
A computer system generates a computer-readable ontology from repository metadata and values, enabling the interpretation of user-entered natural-language statements by associating attributes and values, and performing predefined operations based on the statements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a custom database structure is created for particular customer records, then the repository can efficiently store and organize specific types of information, but the user interface becomes technically complex and requires expert knowledge to operate
Solution Approach 1:
The patent introduces an intermediary layer consisting of natural language processing and ontology generation that mediates between the user and the complex repository structure. Users interact through simple natural language statements rather than directly with the technical database structure, while the system generates ontologies that map these statements to the underlying repository schema, thus preserving storage efficiency while improving accessibility
Solution Approach 2:
The system creates a simplified copy or representation of the repository structure through generated ontologies that mirror the actual data relationships in an accessible format. This ontology copy allows users to interact with a simplified view that preserves the structural integrity and efficiency of the original repository while being much easier to operate
2Stability of the object's composition
If a predefined database template structure is used for information input, then data entry follows a standardized format, but users must adhere to specific formatting rules and the interface remains complex
Solution Approach 1:
The system performs self-service by automatically generating ontologies and interpreting natural language statements without requiring users to manually configure or understand the underlying data structure. The ontology generation process automatically adapts to the repository structure, and the natural language interface automatically handles format validation, eliminating the need for users to follow complex formatting rules while maintaining data consistency
3Ease of operation
If a traditional user interface is generated for repository access, then users can add and modify information, but substantial work effort is required for interface generation and maintenance
Solution Approach 1:
The system performs preliminary action by automatically generating the user interface through ontology creation before any user interaction occurs. The ontology generation process pre-configures the interface structure, data relationships, and interpretation rules, eliminating the need for manual interface design and reduction efforts. This preliminary ontology-based setup enables the system to handle user interactions with minimal additional configuration
Data Source
AI summary
Providing a natural-language interface to a repository includes retrieving information from at least one repository, and generating a computer-readable ontology using the information. The computer-readable ontology is configured for use in interpreting user-entered natural-language statements regarding the at least one repository. A computer system including at least one repository has an ontology-generating module generating a computer-readable ontology using information retrieved from the at least one repository. The ontology may be created in any or all of several forms, such as a separate entity, a pointer structure or an index.