Free-Form Query Engine for Distributed Computing Systems
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Solution Overview
Problem
Conventional search tools in management software require rigid input and domain knowledge, making them inefficient and error-prone for users to search for specific computing system components, especially in complex, distributed environments.
Innovation Solution
A query engine that converts free-form queries into compatible queries for various data sets, allowing users to search without extensive knowledge, providing real-time results and contextually relevant information by analyzing relationships between data elements in graph databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional search tools with rigid input requirements are used, then query precision can be maintained, but ease of operation deteriorates due to requiring domain knowledge and specific criteria
Solution Approach 1:
The patent introduces a natural language processing intermediary layer that translates user-friendly free-form queries into structured search queries. This mediator handles the complexity of query processing internally while presenting a simple interface to users, resolving the contradiction between ease of operation and processing complexity.
Solution Approach 2:
The system changes the parameter of query input from rigid structured formats to flexible natural language. By accepting variable parameters in free-form text and dynamically adapting the processing approach, the system improves ease of operation while managing complexity through automated parsing and query generation.
2Ease of operation
If free-form query conversion is implemented, then ease of operation improves, but reliability deteriorates due to potential conversion errors
Solution Approach 1:
The system implements feedback mechanisms where the converted structured query is validated against the original natural language input. Discrepancies trigger refinement processes, and users can review or correct conversions before execution. This feedback loop maintains reliability while preserving ease of operation.
Solution Approach 2:
The system performs preliminary validation and disambiguation during the conversion process, identifying potential errors before query execution. By catching and correcting issues in advance, the system maintains high reliability while allowing free-form input simplicity.
3Loss of information
If multiple data sets are queried simultaneously, then information completeness improves, but loss of time increases due to processing multiple sources
Solution Approach 1:
The patent merges multiple data set queries into a unified processing operation. By combining search operations across different data sources simultaneously rather than sequentially, the system retrieves comprehensive information while minimizing the time penalty of querying multiple datasets.
Solution Approach 2:
The system adds a dimensional optimization layer that parallelizes query processing across multiple data sets. By operating in an additional processing dimension (parallel execution), the system achieves complete information retrieval without linearly increasing processing time.
Data Source
AI summary
Methods, systems, and computer readable mediums for performing a free-form query are disclosed. According to one exemplary embodiment, a method for performing a free-form query includes receiving free-form information for requesting information about a computing system, converting the free-form information into at least one compatible query for querying at least one data set, querying, using the at least one compatible query, the at least one data set for the information about the computing system, and providing the information about the computing system.