This paper is published in Volume-4, Issue-4, 2018
Area
Big Data
Author
Yousef Alraba'nah
Co-authors
Mohammed Al-refai
Org/Univ
Zarqa University, Zarqa, Jordan, Jordan
Pub. Date
30 August, 2018
Paper ID
V4I4-1496
Publisher
Keywords
Data clustering, Clustering analysis, Hierarchical, Partitioning, Density-Based and Grid-Based

Citationsacebook

IEEE
Yousef Alraba'nah, Mohammed Al-refai. Data clustering algorithms: A second look, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Yousef Alraba'nah, Mohammed Al-refai (2018). Data clustering algorithms: A second look. International Journal of Advance Research, Ideas and Innovations in Technology, 4(4) www.IJARIIT.com.

MLA
Yousef Alraba'nah, Mohammed Al-refai. "Data clustering algorithms: A second look." International Journal of Advance Research, Ideas and Innovations in Technology 4.4 (2018). www.IJARIIT.com.

Abstract

With the huge volume of digital data, clustering algorithms are providing efficient tools for data organizing and analyzing. Clustering algorithms are used in various domains such as bioinformatics, speech recognition, and information retrieval. Clustering is an automatic technique that divides a set of data objects into smaller groups such that the objects within a group are similar to each other and dissimilar to objects in other groups as much as possible. This paper reviews and discusses different clustering algorithms, their concepts, advantages, and limitations. A comparison among clustering algorithms will also be represented based on certain criteria.
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