Event-Based Analysis Engine Historical Data Filtering
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Solution Overview
Problem
Event-based analysis engines face challenges in efficiently utilizing historical information when evaluating rules, particularly when rules require data from multiple events or time periods, leading to unnecessary data processing and potential loss of data during system restarts.
Innovation Solution
A system and method that automatically provides historical data to an event-based analysis engine by filtering out unnecessary events and using a parser, filter, and query component to determine and retrieve required historical information based on rule-specific conditions, ensuring data availability even after system restarts or rule changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all events are provided to the event-based analysis engine for processing, then the engine has complete data available for rule evaluation, but unnecessary data processing occurs and system efficiency decreases
Solution Approach 1:
The patent extracts only the necessary historical events required by specific rules from the complete event stream. The rule evaluation component analyzes each rule to determine which historical events are actually needed, and only those selected events are provided to the event-based analysis engine, eliminating processing of unnecessary data while maintaining data completeness for rule evaluation.
Solution Approach 2:
The patent segments the event processing workflow into distinct components: rule evaluation to determine data requirements, filtering to separate necessary from unnecessary events, and targeted delivery to the analysis engine. This segmentation allows each component to perform its specific function efficiently, with the rule evaluation component identifying exactly what data is needed without processing all events.
2Measurement precision
If historical information is stored and processed for all possible rules, then any rule can be evaluated accurately, but data processing complexity and resource consumption increase
Solution Approach 1:
The patent implements a dynamic approach where the set of historical events provided to the analysis engine changes based on the specific rule being evaluated. Rather than maintaining a static complete dataset, the system dynamically determines and provides only the relevant historical events for each rule, reducing processing complexity while maintaining evaluation accuracy.
Solution Approach 2:
The patent applies local quality by providing different sets of historical events to the analysis engine depending on which rule is being evaluated. Each rule receives a customized, optimized subset of historical data tailored to its specific requirements, rather than all rules receiving the same complete dataset, thereby reducing overall system complexity.
3Speed
If the event-based analysis engine processes events in real-time without historical context, then processing speed is maximized, but rules requiring historical comparison cannot be evaluated
Solution Approach 1:
The patent performs preliminary action by pre-determining which historical events are needed for rule evaluation before the actual analysis occurs. The rule evaluation component analyzes rules and identifies required historical events in advance, allowing the system to efficiently retrieve and provide only those specific events, maintaining processing speed while enabling historical rule evaluation.
Data Source
AI summary
Several aspects for providing historical information to an event based image include a method, an apparatus and an article. One or more of the aspects includes receiving a trigger associated with a rule, determining if the rule requires that historical information be provided to an event-based analysis engine, filtering out events not needed by the rule if the rule requires historical information and providing the event-based analysis engine with historical information based on the filtering.