Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2003
Title: k-means Performance Improvements with Centroid Calculation Heuristics both for Serial and Parallel environments
Authors: Karimov, Jeyhun
Özbayoğlu, Ahmet Murat
Doğdu, Erdoğan
142991
Keywords: k-means
Big Data
Hadoop
MapReduce
Clustering
parallel algorithms
data mining
unsupervised learning
Issue Date: 2015
Publisher: IEEE
Source: Karimov, J., Ozbayoglu, M., & Dogdu, E. (2015, June). K-means performance improvements with centroid calculation heuristics both for serial and parallel environments. In 2015 IEEE International Congress on Big Data (pp. 444-451). IEEE.
Abstract: k-means is the most widely used clustering algorithm due to its fairly straightforward implementations in various problems. Meanwhile, when the number of clusters increase, the number of iterations also tend to slightly increase. However there are still opportunities for improvement as some studies in the literature indicate. In this study, improved implementations of k-means algorithm with a centroid calculation heuristics which results in a performance improvement over traditional k-means are proposed. Two different versions of the algorithm for various data sizes are configured, one for small and the other one for big data implementations. Both the serial and MapReduce parallel implementations of the proposed algorithm are tested and analyzed using 2 different data sets with various number of clusters. The results show that big data implementation model outperforms the other compared methods after a certain threshold level and small data implementation performs better with increasing k value.
Description: 4th IEEE International Congress on Big Data, BigData Congress  ( 2015 : New York City; United States)
URI: https://ieeexplore.ieee.org/document/7207256
https://hdl.handle.net/20.500.11851/2003
ISBN: 978-1-4673-7278-7
ISSN: 2379-7703
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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