Query Generation System Using Expression Type Dictionaries
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Solution Overview
Problem
Existing query generation systems face challenges in searching databases with varying feature expression types, leading to reduced accuracy in retrieving user-intended information, as they require queries to match specific expression types used in each database.
Innovation Solution
A query generation system that includes a processor and database, where the processor applies a dictionary to input character strings to generate queries adaptable to different expression types, enabling searches across multiple databases without constraints on expression types, using feature extraction and classification units to correct and normalize input queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a query is generated using a character string based on the type of expression of features recorded in each database, then the probability of finding user-intended information increases, but the complexity of the query generation system increases due to needing to distinguish and handle multiple expression types
Solution Approach 1:
The patent introduces a dictionary as an intermediary component that maps between different expression types of features. The dictionary stores correspondence relationships between multiple expression types and standard feature representations, allowing the system to handle diverse database expression types without complex processing logic. When a query is generated, the dictionary automatically translates the input character string according to the appropriate expression type, resolving the contradiction by adding a simple mediating layer rather than increasing overall system complexity.
2Measurement precision
If the system applies different dictionaries based on feature expression types, then search accuracy across multiple databases improves, but the processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-building and storing expression type identification rules and dictionary mappings in advance. The system pre-processes and categorizes different feature expression types, storing their correspondence relationships in dictionaries before actual query execution. During query processing, the system quickly identifies the expression type using pre-established rules and retrieves the corresponding dictionary, avoiding time-consuming analysis during the actual search process and thus reducing processing time while maintaining high search accuracy.
3Measurement precision
If the system requires constraints on expression types for query input, then the precision of matching database features improves, but the ease of operation decreases as users must understand and follow expression type constraints
Solution Approach 1:
The patent implements self-service by enabling the system to automatically identify the expression type of the input character string and select the appropriate dictionary without user intervention. The system includes an expression type identification module that automatically analyzes the input query, determines its expression type, and retrieves the corresponding dictionary from pre-stored options. This automatic self-service mechanism eliminates the need for users to understand or specify expression type constraints, maintaining high feature matching precision while significantly improving ease of operation.
Data Source
AI summary
A query generation system includes a database and a processor. The database stores information to be searched, the information being associated with features having multiple types of expressions. The processor is configured to, when a character string to be used to search the database is input without constraint on a type of expression, apply a first dictionary to a character string having a first type of expression, which is included in the input character string, to generate a query for a search from the character string having the first type of expression.


