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...

Celý popis

Podrobná bibliografia

Vydané v:	2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT) s. 25 - 28
Hlavní autori:	Nigro, Libero, Cicirelli, Franco, Franti, Pasi
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 26.09.2022
Predmet:	Benchmark testing Clustering algorithms Clustering methods Clustering problem Java K-Means Lambda Expressions Parallelism Random swap Real-time systems Scalability Sociology Streams
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!