Graph Query Phantom Results Visualization
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Solution Overview
Problem
Graph databases lack effective methods to render and navigate unstructured query results, making it difficult to visualize and manage large datasets, especially when results change over iterations.
Innovation Solution
The system executes multiple queries against a data source to generate result sets, compares them, and modifies the graphical representation by adjusting transparency and visibility of elements based on presence and relevance in subsequent queries, allowing for the visualization of phantom results and efficient navigation of graph database changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If graph databases store data in nodes and edges format, then the data structure becomes flexible and adaptable, but the query results become completely unstructured and difficult to iterate through
Solution Approach 1:
The patent applies visual styling changes to graph elements based on query result relevance. Elements are highlighted or dimmed using color and transparency changes to indicate their importance, making it easier for users to navigate and understand unstructured graph query results by visually distinguishing relevant from irrelevant data
2Quantity of substance
If graph databases store vast amounts of data, then the data capacity increases, but the rendered visual graph becomes nearly useless when large
Solution Approach 1:
The patent extracts and highlights only the relevant portions of large graph databases based on query results. By selectively rendering and styling elements according to their relevance scores, the system enables users to work with manageable visual representations of otherwise overwhelming data quantities
Solution Approach 2:
Visual styling changes based on relevance help users navigate large graphs by emphasizing important elements and de-emphasizing less important ones, making large datasets visually manageable
3Measurement precision
If multiple queries are executed to refine results, then the query precision improves, but the complexity of tracking changes across iterations increases
Solution Approach 1:
The patent uses visual styling changes across query iterations to automatically track and communicate what has changed. Elements are highlighted or dimmed based on their presence and relevance in different query results, providing an intuitive visual history of changes without requiring complex manual tracking
Solution Approach 2:
The system provides visual feedback about query result changes by comparing iterations and highlighting differences. This automatic feedback mechanism reduces the complexity of tracking changes by presenting them in an easily interpretable visual format
Data Source
AI summary
Examples of the present disclosure describe systems and methods of rendering phantom results using graph queries. In aspects, a first query may generate a first result set. The first result set may comprise ordered lists (e.g., node-edge-node 3-tuples), and may be rendered as a graph. A second query may then be executed against the data source to generate a second result set. The first and second result set may be compared. When inconsistencies between the result sets are identified, various degrees of transparency may be used in the graph to indicate the inconsistent data.