ROCK Algorithm Parallelization with TOREADOR Primitives

We present the benefits of applying the code once deploy everywhere approach to clustering of categorical data over large datasets. The paper brings two main contributions: an step-by step application of the code based approach and an enhancement for the ROCK algorithm for clustering categorical dat...

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Vydáno v:2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA) s. 402 - 407
Hlavní autoři: Di Martino, Beniamino, DAngelo, Salvatore, Esposito, Antonio, Cappuzzo, Riccardo, de Oliveira, Anderson Santana
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2018
Témata:
Big Data
clustering
Clustering algorithms
Distributed databases
Labeling
parallelization
ROCK algorithm
Rocks
Skeleton
Storms
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Shrnutí:We present the benefits of applying the code once deploy everywhere approach to clustering of categorical data over large datasets. The paper brings two main contributions: an step-by step application of the code based approach and an enhancement for the ROCK algorithm for clustering categorical data.
DOI:10.1109/WAINA.2018.00119