Visual Event Sequence Analysis for Large-Scale Pattern Discovery

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Solution Overview

Problem

Existing analytical tools lack visual interfaces and functionality to effectively analyze large and diverse sets of event sequences, particularly in business processes, and do not account for time between events, relying on mathematical algorithms instead of visual analysis.

Innovation Solution

A system and method for visually analyzing event sequences by calculating and displaying sequence-specific metrics, allowing end users to reduce sets based on metric values, and enabling customization of visual representations through sorting, color-coding, and machine learning algorithms for grouping and ordering events.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If existing analytical tools are used to analyze event sequences, then mathematical algorithms can process the data, but visual interfaces and functionality to effectively analyze large and diverse sets of event sequences are lacking

Engineering Contradiction:

Improvevisual interface functionalityVSAvoidanalysis capability for large datasets

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The patent replaces traditional mathematical algorithm-based analysis with a visual analysis system that uses graphical interfaces and visual representations to analyze event sequences. The system transforms abstract data processing into visual displays including event sequence diagrams, timelines, and graphical representations that enable intuitive analysis of large datasets without losing analytical capability

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the parameter of data representation from numerical/mathematical format to visual/graphical format. By transforming event sequence data into visual representations with adjustable parameters such as time scales, event grouping levels, and display density, the system enables effective analysis of large and diverse event sequences while maintaining analytical depth

Inventive Principle:

Principle #35Parameter changes

2Ease of manufacture

If process mining tools reverse-engineer sequences into BPMN schemas, then process models can be created, but the variety and peculiarities of actual sequences cannot be understood

Engineering Contradiction:

Improveprocess modeling capabilityVSAvoidability to capture sequence variety

Core Design Contradiction:

Ease of manufactureVSAdaptability or versatility

Solution Approach 1:

The patent segments the event sequences into visual components that can be analyzed at multiple levels. Instead of forcing all sequences into a single BPMN schema, the system divides sequences into manageable visual segments showing individual events, event groups, and pattern repetitions, allowing users to understand both the structured process model and the unique variations in actual sequences

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system adds a visual dimension to process analysis by displaying event sequences in graphical formats that complement traditional BPMN models. This includes temporal dimensions through timelines, spatial dimensions through event positioning, and hierarchical dimensions through grouping levels, enabling simultaneous view of process structure and sequence variety

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Measurement precision

If existing sequence analysis tools are used for life sciences, then biological molecule sequences can be analyzed, but the concept of time between events is not incorporated

Engineering Contradiction:

Improvesequence analysis accuracyVSAvoidtime interval information

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary extraction and preservation of time interval information from event sequences before analysis. By capturing temporal parameters such as time between events, event duration, and sequence timing patterns in advance, the system ensures that time-related information is maintained throughout the visual analysis process rather than being lost in traditional sequence analysis

Inventive Principle:

Principle #10Preliminary action

4Loss of information

If mathematical algorithms are used to discover patterns in sequences, then patterns can be identified, but visual analysis capabilities are not provided

Engineering Contradiction:

Improvepattern discovery capabilityVSAvoidvisual analysis interface

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The patent substitutes mathematical algorithm-based pattern discovery with visual analysis methods that maintain pattern discovery capability while providing intuitive graphical interfaces. The system uses visual pattern recognition, graphical clustering, and visual data mining techniques to identify patterns in event sequences, making the analysis process accessible and interpretable without requiring complex mathematical computations

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12412653B2System and method for visual analysis of event sequences

Publication Date: 2025.09.09 ABBYY DEVELOPMENT INC

AI summary

Techniques are disclosed for creating event sequences from event data and then providing a visual analysis of event sequences. Event-related data for a set of event sequences is analyzed, and event sequences are grouped. Sequence metrics are calculated for the event sequences, and a user interface is provided to display a visual representation of the set of event sequences and the sequence metrics for the set of event sequences.