Query Item Reference for Precise Search Construction
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Solution Overview
Problem
Conventional search applications rely on explicit, database-oriented operators for exact connections between query terms, making it inefficient to define complex queries precisely.
Innovation Solution
The system allows users to associate a first query item as an anchor with a second query item, where the second query item refers to attributes of the first query item, enabling the construction of more precise and efficient search queries by referencing values from the first query item.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search applications use explicit database-oriented operators for exact connections between query terms, then search precision is maintained, but query construction efficiency deteriorates
Solution Approach 1:
The patent introduces an intermediary system that automatically generates and manages search query terms based on user behavior data, transaction data, and contextual information. This intermediary layer between the user and the database eliminates the need for users to manually construct complex queries with explicit operators, while still achieving precise search results through dynamically generated query terms that reflect actual user intent and contextual relationships.
Solution Approach 2:
The system enables self-service search by automatically analyzing user interactions, transaction histories, and contextual data to generate optimized search queries without requiring user expertise in database operators. The system serves itself by learning from user behavior patterns and automatically constructing precise search terms, thereby improving both search precision and query construction efficiency simultaneously.
2Measurement precision
If multiple filters are applied to refine search results, then search accuracy improves, but the complexity of query definition increases
Solution Approach 1:
The system performs preliminary actions by pre-processing user behavior data, transaction data, and contextual information to identify relevant search criteria and relationships before the actual search is executed. This preliminary analysis includes pre-calculating user preferences, transaction patterns, and contextual associations, which are then automatically applied as filters during search operations, eliminating the need for users to manually define complex multi-filter queries.
Solution Approach 2:
An intermediary processing layer automatically manages the complexity of multiple filters by translating user intent and contextual data into optimized filter combinations. This intermediary system analyzes various data sources, determines relevant filtering criteria, and applies them in optimal sequences, thereby achieving high search accuracy without exposing users to the underlying complexity of query definition and filter management.
Data Source
AI summary
A method, user interface, and computer-readable medium to receive a representation of a first query item, the first query item belonging to a data set and having at least one attribute; receive a representation of a second query item, the second query item being defined as relating to at least one particular attribute of another query item; associate the second query item with the first query item; automatically retrieve, in response to the second query item being associated with the first query item, a value for the at least one particular attribute of the second query item from the first query item; and save a record of the retrieved value.