Network Clustering Transient State Analysis for Node Detection

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Solution Overview

Problem

Current network clustering methods only consider the final result and not the transient states, leading to the omission of potential clustering target nodes that are important for the network.

Innovation Solution

An information processing apparatus that acquires and analyzes multiple transient states of a network during clustering, determining common nodes used across these states to improve the detection of clustering target nodes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If only the final result of clustering is considered, then the clustering process is simple and fast, but important clustering target nodes are omitted

Engineering Contradiction:

Improveclustering processing speedVSAvoiddetection accuracy of clustering target nodes

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent applies preliminary action by acquiring information about transient states of the network before finalizing the clustering result. By capturing intermediate states during the clustering process, the system identifies potential clustering target nodes that would be missed if only the final result were considered. This preliminary capture of transient state information enables more accurate detection of important nodes while maintaining processing efficiency.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If transient states during clustering are analyzed, then detection accuracy of clustering target nodes is improved, but processing complexity increases

Engineering Contradiction:

Improvedetection accuracy of clustering target nodesVSAvoidclustering process complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies the extraction principle by isolating and analyzing only the essential transient state information needed for identifying clustering target nodes. Instead of processing all intermediate clustering data, the system extracts specific relevant features from transient states that directly contribute to detecting important nodes. This selective extraction reduces processing complexity while maintaining high detection accuracy.

Inventive Principle:

Principle #2Taking out (Extraction)

3Reliability

If multiple transient states are acquired and analyzed, then completeness of clustering target node detection is improved, but information processing load increases

Engineering Contradiction:

Improvecompleteness of node detectionVSAvoidinformation processing energy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent applies local quality by focusing computational resources on specific regions or aspects of the transient states that are most likely to contain clustering target nodes. Instead of uniformly processing all transient state information, the system identifies and intensively analyzes local portions of the data that have higher probability of containing important nodes. This localized processing approach improves detection completeness while reducing overall energy consumption.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11310144B2Information processing apparatus and non-transitory computer readable medium

Publication Date: 2022.04.19 FUJIFILM BUSINESS INNOVATION CORP

AI summary

An information processing apparatus includes a processor configured to acquire information regarding multiple transient states of a network including multiple nodes when the network undergoes clustering in which the multiple nodes are classified into multiple clusters. The multiple transient states each represent a transient state of the network on a way to a final result of the clustering. The processor is also configured to determine a common node by using the information regarding the acquired multiple transient states. The common node is used in the clustering in the multiple transient states.