Natural Language Alert Generation for Data Storage Systems
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Solution Overview
Problem
Natural language search applications struggle to properly generate and apply domain-specific language (DSL) requests that involve operations other than search queries, limiting users' ability to access and analyze data from diverse data sources without expertise in specific DSLs.
Innovation Solution
A method is developed to generate DSL alert commands based on natural language requests, allowing for the translation and execution of instructions across various data storage systems, enabling users to activate alerts and leverage system capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language search applications are used to enable users to access data from diverse data sources, then ease of operation is improved, but the ability to generate and apply DSL requests involving operations other than search queries deteriorates
Solution Approach 1:
The NL search application is enhanced to perform multiple functions: it can translate natural language search queries to DSL search queries, and additionally translate natural language alert commands to DSL alert commands. This multi-functionality allows the same application to handle both search operations and alert generation, resolving the contradiction by expanding the application's versatility while maintaining ease of operation.
Solution Approach 2:
A translation functionality is introduced as an intermediary component that converts natural language alert commands into executable DSL alert commands. This intermediary translation layer enables users unfamiliar with DSL syntax to still generate complex alert requests, thereby improving both ease of operation and adaptability simultaneously.
2Device complexity
If translation functionality is limited to search queries, then device complexity is reduced, but the ability to provide comprehensive DSL operations deteriorates
Solution Approach 1:
The translation functionality for search queries and alert commands is merged into a single integrated system. The same translation module handles both search query conversions and alert command conversions, eliminating the need for separate translation systems. This merging approach increases comprehensive DSL operation capability without proportionally increasing device complexity.
3Manufacturing precision
If users are required to learn domain-specific languages to access data from specialized data sources, then manufacturing precision of data retrieval is improved, but ease of operation deteriorates
Solution Approach 1:
The natural language to DSL translation functionality acts as an intermediary that converts user-friendly natural language requests into precise DSL commands. This intermediary layer preserves the precision of DSL-based data retrieval while eliminating the need for users to directly learn and use complex DSL syntax, thereby maintaining both ease of operation and data retrieval precision.
Data Source
AI summary
In various embodiments, a natural language (NL) application enables users to more effectively access various data storage systems based on NL requests. As described, the NL application includes functionality for selecting an optimal interpretation algorithm, generating a dashboard, and/or generating an alert based on an NL request. Advantageously, the operations performed by the NL application reduce the amount of time and user effort associated with accessing data storage systems and increase the likelihood of properly addressing NL requests.