Boolean Column Search via Metadata Semantic Mapping
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Solution Overview
Problem
Existing database search systems fail to effectively utilize semantic information from Boolean columns, leading to inefficient keyword searches as terms like 'Yes' or '1' do not accurately identify relevant records due to lack of semantic meaning.
Innovation Solution
The system uses metadata to identify Boolean table columns and convert search terms into conditions that reflect their logical states, thereby enhancing search queries by adding conditions based on the values of these columns, such as '1' representing TRUE and 'No' representing FALSE, to provide semantic meaning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If plain text keyword searching is used on Boolean columns, then the search can be performed, but the search accuracy deteriorates because Boolean values lack semantic information
Solution Approach 1:
The patent introduces metadata as an intermediary layer between the search query and the Boolean column data. The metadata provides semantic descriptions (e.g., 'active status') for Boolean columns, allowing the search system to interpret Boolean values in context. When a search term matches a Boolean column, the system uses the metadata to determine the appropriate Boolean value (TRUE/FALSE) that corresponds to the search intent, thereby recovering semantic information that would otherwise be lost.
2Measurement precision
If semantic information is added to Boolean columns through metadata, then search accuracy improves, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-defining metadata for Boolean columns during database setup or schema definition. The metadata includes semantic descriptions and mappings between search terms and Boolean values. This preliminary configuration allows the search system to automatically utilize semantic information without adding complexity to the runtime search operation, as the interpretation logic is already established in advance.
3Measurement precision
If keyword search terms are converted to logical conditions, then relevance of search results improves, but the complexity of query processing increases
Solution Approach 1:
The patent implements self-service by enabling the search system to automatically detect when a search term corresponds to a Boolean column (through metadata matching) and autonomously convert the keyword search into an appropriate logical condition. The system determines the correct Boolean value (TRUE or FALSE) based on the search term and metadata without requiring manual intervention or complex external processing, thereby managing query processing complexity internally while improving result relevance.
Data Source
AI summary
A system includes reception of a query comprising one or more search terms, determination that one of the one or more search terms corresponds to a table column comprising Boolean operators, determination of a value of the table column corresponding to TRUE, and addition of a condition to the query, the condition specifying the value of the table column.