Abnormal Pattern Analysis Framework with Modular Detection

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing abnormal pattern analysis methods face challenges in efficiently detecting and categorizing abnormal patterns in large datasets, particularly in financial fraud detection, due to increased information complexity and the need for tailored analysis approaches across different service applications.

Innovation Solution

An abnormal pattern analysis method and apparatus that selects appropriate analysis modules based on service applications, utilizing a framework with main and sub-abnormal pattern analysis modules to detect and visualize abnormal patterns, and categorize them into specific analysis groups for effective detection and visualization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a single uniform abnormal pattern analysis method is used across all service applications, then the analysis process is simple and easy to implement, but the detection accuracy decreases for diverse data types and scenarios

Engineering Contradiction:

Improveabnormal pattern detection accuracyVSAvoidanalysis framework complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the abnormal pattern analysis framework into multiple specialized analysis modules, each designed to handle specific types of abnormal patterns or data characteristics. This segmentation allows the system to select appropriate modules for different service applications, improving detection accuracy while managing complexity through modular design.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent implements a dynamic module selection mechanism that adapts the analysis framework based on the characteristics of the input data and service application requirements. The system dynamically determines which analysis modules to activate, transforming the framework from a static uniform structure to a dynamic adaptive one that optimizes accuracy for each specific case.

Inventive Principle:

Principle #15Dynamics

2Reliability

If multiple specialized analysis modules are implemented for different service applications, then the detection accuracy improves for specific data types, but the system complexity and difficulty of operation increase

Engineering Contradiction:

Improveabnormal pattern detection reliabilityVSAvoidsystem operation simplicity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The patent creates a universal abnormal pattern analysis framework that can handle multiple service applications through a common structure with specialized modules. The framework provides multi-functionality by integrating various analysis capabilities while maintaining a unified interface and control mechanism, allowing it to serve diverse applications without requiring separate systems for each.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system implements self-service through automatic module selection and configuration based on the characteristics of the input data and service application. The framework autonomously determines the appropriate analysis modules to use without requiring manual intervention or complex user configuration, thereby maintaining ease of operation while providing specialized analysis capabilities.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If comprehensive analysis modules are used to cover all possible abnormal patterns, then the detection coverage is complete, but the analysis time and processing speed increase

Engineering Contradiction:

Improveabnormal pattern detection coverageVSAvoidanalysis processing speed

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent applies partial action by implementing selective module execution where only the necessary analysis modules are activated based on the specific service application and data characteristics. Instead of running all possible analysis modules for every case, the system performs partial analysis using only the relevant modules, thereby maintaining comprehensive coverage capability while improving processing speed for each specific case.

Inventive Principle:

Principle #16Partial or excessive action

4Measurement precision

If tailored analysis approaches are developed for each service application, then the detection accuracy for that application improves, but the development time and resource requirements increase

Engineering Contradiction:

Improveapplication-specific detection accuracyVSAvoidsystem development time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent develops a universal abnormal pattern analysis framework that serves multiple service applications through a common architecture with configurable specialized modules. This approach eliminates the need to develop separate analysis systems for each application, significantly reducing development time and resource requirements while still providing application-specific detection accuracy through module configuration and selection.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10032167B2Abnormal pattern analysis method, abnormal pattern analysis apparatus performing the same and storage medium storing the same

Publication Date: 2018.07.24 LG CNS CO LTD

AI summary

An abnormal pattern analysis method includes determining a service application associated with analysis data, selecting at least one abnormal pattern analysis module in an abnormal pattern analysis framework based on the determined service application and performing an analysis for the analysis data through the selected at least one abnormal pattern analysis module to detect an abnormal pattern.