Natural Language Multidimensional Database Query Generation
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Solution Overview
Problem
Users face challenges in generating multidimensional database queries due to the complexity of relational database queries and the need for extensive knowledge of query language syntax and database structure, especially when using multidimensional databases, which can be difficult to express and require manual writing or limited user interface options.
Innovation Solution
A system that generates multidimensional database queries based on user-supplied natural language queries using dictionary data structures, which map literals to dimensions and members, allowing for the combination of members across different dimensions and incorporating importance scores to enhance query relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually write MDDB queries or use wizard interfaces, then query functionality is achieved, but user knowledge requirements and system complexity increase
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates user-friendly natural language queries into MDDB query syntax. This mediator layer handles the complexity of dimension and member mappings, allowing users to query without knowing the underlying MDDB structure or syntax while the system manages the translation complexity behind the scenes.
2Ease of operation
If wizard interfaces with predetermined options are used, then query structure is guided, but query flexibility and precision are limited
Solution Approach 1:
The patent implements a dynamic query generation system that adapts to user needs. Instead of fixed wizard options, the system dynamically generates MDDB queries based on natural language input, allowing users to express precise query intentions while the system adapts the underlying query structure to match the user's specific needs and the database schema.
3Ease of operation
If natural language processing is implemented, then user knowledge requirements are reduced, but processing complexity and computational resources increase
Solution Approach 1:
The patent performs preliminary processing by pre-defining dimension and member mappings in the system. This preliminary setup allows the natural language processing to focus on translating user intent rather than interpreting raw database schemas, reducing the computational complexity during actual query execution while still lowering user knowledge requirements.
Data Source
AI summary
Techniques for generating a multidimensional database query are disclosed. A system receives a user-supplied natural language query and performs natural language processing to extract a literal from the natural language query. The system performs a lookup of the literal in one or more dictionary data structures associated with a multidimensional database, to determine that the literal is associated with a particular dimension of multiple dimensions in the multidimensional database. The system performs a lookup of the literal and the dimension in the one or more dictionary data structures, to determine that the literal is associated with a particular member of the dimension. The system generates a multidimensional database query to satisfy the user-supplied natural language query. The multidimensional database query includes a query clause that references the particular member of the dimension.