Abstract
Clustering can be defined as the process of partitioning a set of patterns into disjoint and homogeneous meaningful groups (clusters). There is a growing need for parallel algorithms in this field since databases of huge size are common nowadays. This paper presents a parallel version of a recently proposed algorithm that has the ability to scale very well in parallel environments.
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Tasoulis, D.K., Alevizos, P.D., Boutsinas, B., Vrahatis, M.N. (2003). Parallel Unsupervised k-Windows: An Efficient Parallel Clustering Algorithm. In: Malyshkin, V.E. (eds) Parallel Computing Technologies. PaCT 2003. Lecture Notes in Computer Science, vol 2763. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45145-7_32
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DOI: https://doi.org/10.1007/978-3-540-45145-7_32
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