Abstract Query Generation for Structured Data Search
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Solution Overview
Problem
Current search techniques are not optimized for creating queries for abstract structured datasets, often returning only unstructured data that matches a search query, and require specialized user knowledge, making them inaccessible to non-expert users and complicated for trained users when dealing with business intelligence data.
Innovation Solution
A computer-readable storage medium with executable instructions that extracts data model object information and report data values to define indexed fields, allowing for the generation of abstract queries that match data model objects and report data values, enabling effective searching of abstract structured data sources and reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If state of the art search techniques are used for searching unstructured datasets, then direct data matching is achieved, but the ability to create abstract queries for structured datasets is lost
Solution Approach 1:
The patent introduces an intermediary layer that translates natural language search queries into structured query language (SQL) or other query formats. This intermediary translation layer enables users to search structured datasets using simple natural language while the system automatically generates the appropriate abstract queries, thus resolving the contradiction between ease of operation and adaptability.
2Measurement precision
If specialized user knowledge is required for query specification and report design, then precise data retrieval is achieved, but accessibility to non-expert users is reduced
Solution Approach 1:
The system provides self-service capabilities through automated query generation from natural language inputs, intelligent data source discovery, and automatic report design. The system serves itself by translating user intent into technical queries without requiring user expertise in query specification or report design, thus maintaining precision while improving accessibility.
Solution Approach 2:
The patent replaces the mechanical system of manual query writing and report design with an automated intelligent system that uses natural language processing and machine learning to generate queries and design reports automatically, eliminating the need for specialized user knowledge while maintaining retrieval accuracy.
3Productivity
If report documents are designed to access and format external data, then data presentation capability is improved, but complexity of working with data sources increases
Solution Approach 1:
The system performs preliminary actions by automatically discovering available data sources, pre-generating query structures, and pre-designing report templates based on user intent. This preliminary automation of complex tasks reduces the actual complexity users experience while maintaining high data presentation efficiency.
Data Source
AI summary
A computer readable storage medium includes executable instructions to extract data model object information and report data values from data model objects in at least one semantic abstraction to define indexed fields. A search query is received. The search query is applied against the indexed fields to define matching data model objects and matching report data values. A proposed abstract query with at least one matching data model object and a corresponding semantic abstraction is generated.