Culture-Dependent Data Filtering via Dynamic Type Interpretation
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Solution Overview
Problem
Existing database querying systems require complex structured queries that are sensitive to database schema and often fail to handle culture-dependent and inexact user inputs, leading to incomplete or incorrect search results.
Innovation Solution
A user interface that allows users to enter filter terms to filter data results, interpreting culture-dependent meanings and automatically selecting relevant columns, creating a sophisticated query to retrieve desired data without specifying search locations or methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional SQL queries are used to search structured databases, then precise data retrieval is achieved, but the query complexity and user expertise requirements increase significantly
Solution Approach 1:
The patent introduces an intermediary layer between the user and the database that automatically converts simple user-friendly filter terms into sophisticated SQL queries. This intermediary handles the complexity of query construction, schema understanding, and cultural format conversion, while users only need to provide simple search terms like '1.23' or '1/12/2010' without knowing the underlying database structure or SQL syntax.
2Reliability
If strict data type matching is enforced in database queries, then data accuracy is maintained, but relevant results are missed due to cultural format differences and inexact user input
Solution Approach 1:
The patent dynamically changes the interpretation parameters of user input based on cultural context and data type analysis. When a user enters '1.23', the system analyzes the target column's data type and adjusts the search parameter accordingly - treating it as a numeric value for numeric columns, or as a date format for date columns (interpreting it as January 23rd). This allows the same input to correctly match different data types without compromising data accuracy.
Solution Approach 2:
The patent applies partial matching strategies where the search term '1.23' is expanded to search for values like '1.230', '1.232', or any numeric value containing the sequence '1.23'. This excessive action of searching for multiple possible matches ensures that relevant results are not missed due to minor formatting differences or imprecise user input, while still maintaining data reliability through type-aware matching.
3Measurement precision
If users must specify exact column locations and search methods, then query precision is improved, but ease of operation deteriorates due to schema knowledge requirements
Solution Approach 1:
The patent enables the query system to serve itself by automatically analyzing the user's simple filter term, determining the appropriate data types and columns to search, and constructing the optimal query without user intervention. The system self-determines which columns contain the relevant data based on data type matching and automatically handles the complexity of schema navigation, making the operation as simple as entering a search term while maintaining precise search capability.
4Reliability
If culture-specific date and number formats are strictly interpreted, then data integrity is preserved, but adaptability to different user cultures decreases
Solution Approach 1:
The patent performs preliminary analysis of the user's cultural context and the target column's data type before executing the search. When a user enters a date or number format, the system proactively determines the appropriate interpretation based on the user's cultural background and the column's expected data type, converting the input into the correct format for database matching. This preliminary cultural adaptation happens automatically, preserving data integrity while accommodating diverse user cultures.
Data Source
AI summary
Technologies are described herein for filtering data in a result set using inexact and/or culture dependent terms. A user provides one or more filter terms for filtering a result set being viewed. One or more data type interpretations are determined for each filter term based on the value of the term. The data type interpretations may further be based on a locale associated with the user. For each filter term, the columns of the result set to which the filter term is to be applied is selected based on the data type interpretations determined for the filter term and the data types of the columns. The filter terms are then applied to the selected columns of the result set, thus causing the rows of the result set as displayed to the user to be limited to rows wherein at least one column value satisfies a filter term.