Efficient and Reliable Clustering by Parallel Random Swap Algorithm

Solving large-scale clustering problems requires an efficient algorithm which can be implemented also in parallel. K-means would be suitable but it can lead to an inaccurate clustering result. To overcome this problem, we present a parallel version of random swap clustering algorithm. It combines th...

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Veröffentlicht in:	2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT) S. 25 - 28
Hauptverfasser:	Nigro, Libero, Cicirelli, Franco, Franti, Pasi
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 26.09.2022
Schlagworte:	Benchmark testing Clustering algorithms Clustering methods Clustering problem Java K-Means Lambda Expressions Parallelism Random swap Real-time systems Scalability Sociology Streams
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