Live Event Feed Interface for Real-Time Drill-Down Analysis
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Solution Overview
Problem
Existing systems lack an efficient and interactive way to provide real-time access to event-based information from multiple sources, allowing for user interaction and personalized analysis.
Innovation Solution
An interactive event-based information system with a live feed and drill-down interface that extracts, stores, and publishes event data, enabling user interaction and personalized analysis through a browser-based interface and automated profiling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If event information is continuously extracted and published from multiple sources in real-time, then information freshness and relevance are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments event information processing into distinct modules: extraction interface for collecting events from multiple sources, event-based data store for organized storage, and publication interface for selective publishing. This segmentation allows real-time processing while managing system complexity through modular architecture.
Solution Approach 2:
An event-based data store acts as an intermediary layer between the extraction interface and publication interface. This mediator buffers, organizes, and manages event data, enabling continuous real-time extraction and publishing while simplifying the coordination between multiple sources and outputs.
2Ease of operation
If users can interact with and drill down into event information, then user engagement and information accessibility are improved, but interface complexity increases
Solution Approach 1:
The system adds a temporal dimension to event information display by presenting events in chronological order with timestamps. This dimensional approach allows users to easily navigate and drill down into event details based on time-based organization, enhancing accessibility without significantly increasing interface complexity.
3Loss of information
If personalized analysis and user contributions are enabled, then information relevance and user value are improved, but data management and processing requirements increase
Solution Approach 1:
The event-based data store serves multiple functions: storing extracted events, organizing user-contributed analysis, and providing data for both automated publishing and personalized user access. This multi-functionality allows the system to handle personalized analysis and user contributions without requiring separate dedicated systems, managing data processing requirements efficiently.
Data Source
AI summary
In one general aspect, an interactive event-based information system is disclosed that includes an event-based data store for storing information about events selectively extracted from a plurality of machine-readable information sources. A live feed extraction interface is responsive to the event-based data store and has a feed publication output operative to publish a live feed of selected information about events. A live event feed user interface includes a live feed display interface operative to present a succession of visual information elements corresponding to events covered in the live event feed, and a drill-down interface responsive to user interaction to provide access to further information about the information elements from the data store.