Database Natural Language Support via Data Abstraction Model
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Solution Overview
Problem
Conventional database environments face challenges in providing flexible and efficient natural language support, as changes to the underlying database require rewriting the natural language support layer, making it difficult to maintain and update.
Innovation Solution
A data abstraction model is used to define logical fields that describe physical data, associated with a language resource component providing natural language expressions and translation information, allowing for the display of queries in various languages and formats suitable for different user groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language support is provided at the application level, then users can interact with the database in natural language, but rewriting the natural language support layer is required when changes are made to the underlying database
Solution Approach 1:
The patent introduces a data abstraction model as an intermediary layer between the natural language support layer and the underlying database. This abstraction model translates natural language queries into database operations without requiring changes to the natural language support layer when the database schema changes, thus resolving the contradiction between ease of operation and maintenance complexity
Solution Approach 2:
The patent segments the system into distinct layers: the natural language support layer, the data abstraction model layer, and the underlying database layer. This segmentation allows each layer to be independently maintained and updated, preventing ripple effects when changes are made to the database schema
2Adaptability or versatility
If the data abstraction model is associated with language resource components, then queries can be displayed in multiple languages and formats, but the system complexity increases
Solution Approach 1:
The data abstraction model is designed to be universal and multi-functional, capable of working with multiple language resource components and database types. This universality allows the same abstraction model to support multiple languages and formats without requiring separate implementations for each language, thus managing system complexity while achieving versatility
Solution Approach 2:
The system manages complexity by parameterizing the language and format characteristics rather than implementing separate systems for each language. The data abstraction model uses configurable parameters to switch between different language resource components, allowing flexible adaptation without proportional increase in system complexity
Data Source
AI summary
A method, system and article of manufacture for data processing in databases and, more particularly, for providing natural language support in a database environment. One embodiment provides a method of providing natural language support for users running queries against a database. The method comprises providing a data abstraction model comprising a plurality of logical fields abstractly describing physical data residing in the database, and associating the data abstraction model with a language resource component defining a natural language expression for each of the plurality of logical fields.