Event Sequence Visualization for Time-Aware Pattern Analysis

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Solution Overview

Problem

Existing analytical tools lack visual interfaces and functionality to effectively analyze event sequences, particularly in large and diverse sets, and fail to incorporate time-based patterns and deviations, limiting their ability to understand business processes and discover common denominators.

Innovation Solution

A system and method for visually analyzing event sequences by calculating and displaying sequence-specific metrics, allowing end users to filter and manipulate event sets using a user interface, and employing machine learning to group and order sequences based on predetermined criteria.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If existing analytical tools are used to analyze event sequences, then general business intelligence or process mining can be performed, but visual interfaces and functionality to visualize and analyze sequences are lacking

Engineering Contradiction:

Improvevisual interface functionalityVSAvoidsequence analysis capability

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The patent replaces traditional mechanical data analysis methods with visual display technology. Event sequences are transformed into visual representations showing temporal relationships, event types, and patterns through graphical interfaces, allowing users to see sequence structures rather than just tabular data

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces sequence analysis as an intermediary layer between raw event data and business intelligence insights. This intermediary functionality processes event sequences to extract patterns, deviations, and temporal relationships, then presents them through visual interfaces that bridge the gap between data and understanding

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of manufacture

If process mining tools reverse-engineer sequences into BPMN schemas, then process models can be discovered, but the variety and peculiarities of actual sequences are lost

Engineering Contradiction:

Improveprocess model discoveryVSAvoidsequence variety and peculiarities

Core Design Contradiction:

Ease of manufactureVSLoss of information

Solution Approach 1:

The patent segments the analysis into two complementary views: process model discovery for common patterns and individual sequence visualization for peculiarities. This segmentation allows simultaneous preservation of both aggregated process knowledge and individual sequence characteristics without forcing all sequences into a single schema

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent adds a visual dimension to sequence analysis that complements the schematic dimension of BPMN. By displaying sequences in both process model space and visual temporal space, the system preserves information about sequence variety and peculiarities that would be lost in schema-only representations

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 time-based patterns and deviations are not incorporated

Engineering Contradiction:

Improvesequence analysis accuracyVSAvoidtime-based analysis capability

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent changes the analytical parameters from static sequence composition to dynamic temporal patterns. By incorporating time-based metrics such as event timing, duration, frequency, and temporal relationships, the system adapts sequence analysis to capture time-aware patterns while maintaining measurement precision through structured temporal data processing

Inventive Principle:

Principle #35Parameter changes

4Productivity

If mathematical algorithms are used to discover patterns in sequences with large numbers of elements, then pattern discovery can be performed, but visual analysis is not available

Engineering Contradiction:

Improvepattern discovery efficiencyVSAvoidvisual analysis capability

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The patent merges mathematical algorithm-based pattern discovery with visual analysis capabilities. Automated algorithms process large sequences to identify patterns and deviations, then these results are presented through visual interfaces that allow users to see, verify, and interact with the discovered patterns, combining the efficiency of computation with the insight of visualization

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20250356996A1System and method for visual analysis of event sequences

Publication Date: 2025.11.20 ABBYY DEVELOPMENT INC

AI summary

Techniques are disclosed for receiving, from one or more data sources, event-related data for a set of event sequences; selecting one or more event grouping criteria from a list of event grouping criteria, wherein the list of event grouping criteria comprises a criterion of grouping by an event location, a criterion of grouping by an event entity, and a criterion of grouping by an event time; grouping, into one or more groups, event sequences within the set of event sequences based on the one or more event grouping criteria; calculating sequence metrics for each group of the one or more groups of the event sequences within the set of event sequences; and displaying, on a user interface, the sequence metrics for the set of event sequences.