Automated Event Relationship Identification System
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Solution Overview
Problem
Manual processes for tracking and identifying relationships between events are inexact and time-consuming, lacking efficiency in automated systems.
Innovation Solution
A computer system that stores relationship definitions with selectors and constraints, evaluates events against these definitions, and converts candidate relationships to instances when minimum matching events are received, enabling automated identification and management of event relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processes are used to track and identify relationships between events, then flexibility and adaptability are maintained, but time consumption increases and precision decreases
Solution Approach 1:
The patent replaces manual mechanical processes with an automated computer-based system that uses event selectors, relationship definitions, and automated matching algorithms to identify relationships between events, thereby eliminating human error and time consumption associated with manual tracking
Solution Approach 2:
The system enables automated self-service relationship identification by automatically receiving events, evaluating them against stored relationship definitions, creating candidate relationships, and converting them to relationship instances without requiring manual intervention at each step
2Productivity
If automated event processing is implemented, then productivity and speed improve, but system complexity increases
Solution Approach 1:
The patent segments the automated relationship identification process into distinct modular components: event receiving module, event evaluation module, candidate relationship creation module, and relationship instance conversion module. Each module performs a specific function, making the complex system manageable and maintainable while preserving high productivity
Solution Approach 2:
The system employs universal relationship definitions and event selectors that can be reused across multiple event types and relationship scenarios. This multi-functionality allows the same core infrastructure to handle diverse relationship identification tasks, reducing overall system complexity while maintaining high processing capacity
3Reliability
If comprehensive relationship definitions with multiple constraints are stored, then measurement precision and reliability improve, but device complexity and information storage requirements increase
Solution Approach 1:
The patent uses parameter-based relationship definitions where relationships are defined by configurable parameters such as event selectors, constraints, and matching criteria. These parameters can be adjusted and customized without changing the underlying system structure, allowing high reliability through precise parameter specification while maintaining manageable complexity through parameterization
Data Source
AI summary
According to an example implementation, a non-transitory computer-readable storage medium is provided that includes computer-readable instructions stored thereon that, when executed, are configured to cause a processor to at least: store a relationship definition including one or more selectors identifying events participating in the relationship and one or more constraints between the events, at least one of the constraints expressed in terms of one or more relationship parameters. The instructions further cause the processor to receive one or more events, evaluate the received events against the one or more selectors, create a candidate relationship when the relationship parameters have been defined based on receiving one or more events that match one or more of the selectors, and convert the candidate relationship to a relationship instance when a minimum number of events matching each of the selectors are received.