Search Interface with Precomputed Knowledge Graph for Low Latency
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Solution Overview
Problem
Conventional search engines face challenges in efficiently processing and displaying data related to events, leading to high latency and resource-intensive operations, particularly when predicting outcomes in real-time, due to the need to traverse extensive knowledge graphs for each query and requiring multiple user interfaces and research tools.
Innovation Solution
A data processing system that generates rendering data for a graphical user interface, featuring a knowledge graph stored in volatile memory with a main stem graph and child graphs, allowing for near real-time query processing and data overlay techniques to condense information into a single interface, reducing bandwidth and computational resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines traverse extensive knowledge graphs for each query to predict outcomes in real-time, then measurement precision and reliability are improved, but loss of time and productivity deteriorate due to high latency
Solution Approach 1:
The system pre-computes and stores event-outcome pairs in a knowledge graph before queries are received. When an event occurs, the system performs a lookup of pre-computed outcomes rather than traversing the knowledge graph in real-time, dramatically reducing latency while maintaining prediction accuracy
Solution Approach 2:
The knowledge graph is segmented into event types and outcome pairs, allowing the system to quickly identify and retrieve relevant pre-computed results for specific event types without processing the entire knowledge graph structure
2Loss of information
If conventional search engines use multiple user interfaces and research tools to display event data, then information completeness is improved, but device complexity and loss of information increase
Solution Approach 1:
The system consolidates multiple research tools and user interfaces into a single unified interface that displays event data, outcome predictions, and historical information together. This merging maintains complete information while reducing the complexity of navigating multiple separate tools
Solution Approach 2:
The single user interface is designed to perform multiple functions: displaying real-time event data, showing pre-computed outcome predictions, presenting historical event patterns, and providing search capabilities all in one unified view, eliminating the need for multiple specialized tools
3Adaptability or versatility
If conventional search engines process queries in real-time without preprocessing, then adaptability is improved, but productivity and loss of time worsen due to resource-intensive operations
Solution Approach 1:
The system pre-processes event data during off-peak times to compute outcome predictions and store them in the knowledge graph. This preliminary processing enables rapid retrieval during actual query operations, improving both speed and resource efficiency while maintaining adaptability through the structured organization of pre-computed results
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating rendering data that when rendered on a display device presents a graphical user interface that displays a first visual representation of a value curve, a time period selection window that is configured to move along the first visual representation of the value curve to select one or more portions of the first visual representation of the value curve, a second visual representation of the value curve that is based on the selected one or more portions of the first visual representation of the value curve, a first events bar that includes two or more first event icons that are each associated with a different type of event, and a second events bar that includes two or more second event icons that are each associated with a same type of event.