An Accelerated MapReduce-Based K-prototypes for Big Data

Abstract

Big data are often characterized by a huge volume and a variety of attributes namely, numerical and categorical. To address this issue, this paper proposes an accelerated MapReduce-based k-prototypes method. The proposed method is based on pruning strategy to accelerate the clustering process by reducing the unnecessary distance computations between cluster… (More)
DOI: 10.1007/978-3-319-50230-4_2

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Cite this paper

@inproceedings{HajKacem2016AnAM, title={An Accelerated MapReduce-Based K-prototypes for Big Data}, author={Mohamed Aymen Ben HajKacem and Chiheb-Eddine Ben N'cir and Nadia Essoussi}, booktitle={STAF Workshops}, year={2016} }