Query Classification Engine for Database Search
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Solution Overview
Problem
Users face inefficiencies in searching databases due to the need for specific search formats, such as SQL, which may be unknown to them, and lack of visibility into the database schema, leading to suboptimal search results and repetitive queries.
Innovation Solution
A unified search interface that classifies user queries as either natural language or keyword queries based on internal and external factors, including query terms and contextual information, allowing the system to determine the appropriate search technique without user specification, and provides query remediation suggestions to improve results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are required to use specific search formats like SQL, then search precision can be improved, but ease of operation deteriorates because users lack knowledge of database schemas and search syntax
Solution Approach 1:
The system introduces a classification engine as an intermediary between the user's natural language query and the database search execution. This engine automatically classifies queries into different types (e.g., keyword search, natural language query, SQL-like query) and transforms them into appropriate search formats, eliminating the need for users to directly use complex SQL syntax while maintaining search precision
Solution Approach 2:
The system enables self-service by automatically analyzing and classifying user queries without requiring user intervention or knowledge of database schemas. The classification engine autonomously determines the appropriate search strategy and executes the query, allowing users to benefit from precise database searching while maintaining simple natural language interaction
2Measurement precision
If the system provides detailed database schema information to users, then search precision improves, but device complexity increases due to the need for schema visibility and management interfaces
Solution Approach 1:
The system extracts only the essential schema information needed for query classification and execution, separating it from the complete database schema. The classification engine accesses specific schema metadata (table names, column names, data types) relevant to the query without exposing the entire database structure to users, thereby maintaining search precision while reducing system complexity
Solution Approach 2:
The classification engine serves as an intermediary that handles schema interpretation and translation. It internally processes schema information to understand data relationships and structures, then translates complex schema concepts into simple user-friendly query classifications without requiring users to interact with or understand the underlying schema complexity
3Loss of information
If users perform multiple repetitive searches to find relevant results, then search completeness improves, but loss of time increases
Solution Approach 1:
The system performs preliminary query classification and analysis before executing the actual search. The classification engine pre-processes the user's natural language query, identifies the intended search type, and prepares the appropriate search strategy in advance, ensuring that the first search attempt is optimized and reduces the need for multiple repetitive searches
Solution Approach 2:
The system implements feedback mechanisms where the classification engine learns from query patterns and user interactions. By analyzing successful query classifications and user corrections, the system continuously improves its classification accuracy, leading to better search results on subsequent queries and reducing the time users spend on repetitive search attempts
Data Source
AI summary
In disclosed techniques, a computing system causes presentation of a user interface having an input field operable to receive, from a user, a search query for a database. The computing system may classify the search query by: determining whether the search query includes terms that are within a specified vocabulary indicative of a natural language query and determining whether the search query includes terms that identify an object defined in a schema of the database. In response to classifying the search query as a natural language query, the computing system returns query results determined by identifying values in the database corresponding to the object defined in the schema. In response to classifying the search query as a keyword query, the computing system returns query results determined by comparing terms of the search query to values within records in the database.