Dynamic GUI Data Object Filtering via Attribute Exclusion
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Solution Overview
Problem
Existing graphical user interfaces (GUIs) face challenges in efficiently navigating large datasets, as they often present users with overwhelming amounts of data, making it difficult to find specific objects due to the need for manual scrolling or repetitive search queries to filter results.
Innovation Solution
A method and system that dynamically updates a GUI by allowing users to select an object, identify its attribute parameters, and exclude similar objects based on these parameters, reducing the dataset to a more manageable size through dynamic rendering and filtering, thereby improving user interaction and data presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a user searches for objects using multiple keywords in a large dataset, then the search precision improves, but the time required to find the desired object increases due to the need to enter multiple search terms and repeatedly filter results
Solution Approach 1:
The system pre-calculates and stores similarity metrics between objects based on their attribute parameters before the user performs a search. When a user selects an object, the system can immediately present similar objects for exclusion without requiring multiple iterative search queries, thus reducing the time to find the desired object while maintaining search precision
Solution Approach 2:
The system dynamically updates the set of presented objects based on user selections in real-time. After each selection, the system automatically excludes similar objects and presents the next most relevant results, adapting the search process to user preferences without requiring manual re-querying, thereby reducing time loss while preserving precision
2Loss of information
If the GUI presents all matching objects from a large dataset, then the completeness of information is improved, but the ease of operation deteriorates due to overwhelming amounts of data requiring manual scrolling
Solution Approach 1:
The system extracts and excludes objects that are similar to the user's selection from the presented set. By removing these redundant similar objects after each selection, the system maintains information completeness for the remaining unique options while significantly reducing the total number of objects the user must scroll through, thereby improving navigation ease
Solution Approach 2:
Instead of presenting all objects and requiring users to manually filter them, the system inverts the approach by automatically excluding similar objects based on user selections. This inversion transforms the user experience from active filtering to passive reception of refined results, improving ease of operation while preserving access to all non-similar matching objects
3Adaptability or versatility
If the system presents a large number of objects in the GUI, then the variety of options is improved, but the device complexity increases due to higher processor utilization and data traffic requirements
Solution Approach 1:
The system applies partial exclusion by removing only the similar objects that would create redundancy, rather than filtering out all objects except the top match. This partial action maintains a diverse set of unique options for users while reducing the overall data volume and processing requirements, thereby lowering device complexity while preserving option variety
Solution Approach 2:
The system changes the parameter of the presented dataset by dynamically adjusting the set of displayed objects based on user selections. By modifying which objects are included or excluded from the presentation based on similarity parameters, the system maintains variety in the options shown while reducing the total data volume and associated processing complexity
Data Source
AI summary
There is provided a method for dynamically updating a set of data objects, comprising: managing an object dataset defining attribute values for attribute parameters for each object; receiving a query including search term(s); applying the query to the object dataset to select a first set of objects including attribute parameter(s) associated with the search term(s); instructing rendering of the first set of objects within a graphical user interface (GUI); receiving a selection of object(s) of the first set of objects; identifying attribute parameter(s) according to the selected object(s); excluding a second set of objects from the first set of objects based on different attribute values of the identified attribute parameter(s), to identify a third set of objects; and instructing dynamic rendering to update the GUI to present the third set of objects, wherein the third set of objects includes fewer members than the first set of objects.