Enhancement of the K-means Algorithm for Mixed Data in Big Data Platforms

Oded Koren; Carina Antonia Hallin; Nir Perel; Dror Bendet

doi:10.1007/978-3-030-01054-6_71

Enhancement of the K-means Algorithm for Mixed Data in Big Data Platforms

Oded Koren, Carina Antonia Hallin, Nir Perel, Dror Bendet

Department of International Economics, Government and Business

Shenkar College of Engineering and Design

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Big data research has emerged as an important discipline in information systems research and management. Yet, while the torrent of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts, research indicates there is an increasing need to develop more efficient algorithms for treating mixed data in big data. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm which handles the problem of mixed data. We then utilize big data platforms to implement the algorithm. This provides us with a solid basis for performing more targeted profiling for business and research purposes using big data, so that decision makers will be able to treat mixed data, i.e. numerical and categorical data, to explain phenomena within the big data ecosystem.

Original language	English
Title of host publication	Intelligent Systems and Applications : Proceedings of the 2018 Intelligent Systems Conference (IntelliSys). Volume 1
Editors	Kohei Arai, Supriya Kapoor, Rahul Bhatia
Number of pages	16
Place of Publication	Cham
Publisher	Springer
Publication date	2019
Pages	1025-1040
ISBN (Print)	9783030010539
ISBN (Electronic)	9783030010546
DOIs	https://doi.org/10.1007/978-3-030-01054-6_71
Publication status	Published - 2019
Event	6th Intelligent Systems Conference. IntelliSys - London, United Kingdom Duration: 6 Sept 2018 → 7 Sept 2018 Conference number: 6 http://saiconference.com/IntelliSys

Conference

Conference	6th Intelligent Systems Conference. IntelliSys
Number	6
Country/Territory	United Kingdom
City	London
Period	06/09/2018 → 07/09/2018
Internet address	http://saiconference.com/IntelliSys

Series	Advances in Intelligent Systems and Computing
Number	868
ISSN	2194-5357

Keywords

Big data
Mixed data
Hadoop
K-means

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Koren, Oded ; Hallin, Carina Antonia ; Perel, Nir et al. / Enhancement of the K-means Algorithm for Mixed Data in Big Data Platforms. Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys). Volume 1. editor / Kohei Arai ; Supriya Kapoor ; Rahul Bhatia. Cham : Springer, 2019. pp. 1025-1040 (Advances in Intelligent Systems and Computing; No. 868).

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title = "Enhancement of the K-means Algorithm for Mixed Data in Big Data Platforms",

abstract = "Big data research has emerged as an important discipline in information systems research and management. Yet, while the torrent of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts, research indicates there is an increasing need to develop more efficient algorithms for treating mixed data in big data. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm which handles the problem of mixed data. We then utilize big data platforms to implement the algorithm. This provides us with a solid basis for performing more targeted profiling for business and research purposes using big data, so that decision makers will be able to treat mixed data, i.e. numerical and categorical data, to explain phenomena within the big data ecosystem. ",

keywords = "Big data, Mixed data, Hadoop, K-means, Big data, Mixed data, Hadoop, K-means",

author = "Oded Koren and Hallin, {Carina Antonia} and Nir Perel and Dror Bendet",

year = "2019",

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booktitle = "Intelligent Systems and Applications",

address = "Germany",

note = "6th Intelligent Systems Conference. IntelliSys ; Conference date: 06-09-2018 Through 07-09-2018",

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Koren, O, Hallin, CA, Perel, N & Bendet, D 2019, Enhancement of the K-means Algorithm for Mixed Data in Big Data Platforms. in K Arai, S Kapoor & R Bhatia (eds), Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys). Volume 1. Springer, Cham, Advances in Intelligent Systems and Computing, no. 868, pp. 1025-1040, 6th Intelligent Systems Conference. IntelliSys, London, United Kingdom, 06/09/2018. https://doi.org/10.1007/978-3-030-01054-6_71

Enhancement of the K-means Algorithm for Mixed Data in Big Data Platforms. / Koren, Oded; Hallin, Carina Antonia; Perel, Nir et al.
Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys). Volume 1. ed. / Kohei Arai; Supriya Kapoor; Rahul Bhatia. Cham: Springer, 2019. p. 1025-1040 (Advances in Intelligent Systems and Computing; No. 868).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AB - Big data research has emerged as an important discipline in information systems research and management. Yet, while the torrent of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts, research indicates there is an increasing need to develop more efficient algorithms for treating mixed data in big data. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm which handles the problem of mixed data. We then utilize big data platforms to implement the algorithm. This provides us with a solid basis for performing more targeted profiling for business and research purposes using big data, so that decision makers will be able to treat mixed data, i.e. numerical and categorical data, to explain phenomena within the big data ecosystem.

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Koren O, Hallin CA, Perel N, Bendet D. Enhancement of the K-means Algorithm for Mixed Data in Big Data Platforms. In Arai K, Kapoor S, Bhatia R, editors, Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys). Volume 1. Cham: Springer. 2019. p. 1025-1040. (Advances in Intelligent Systems and Computing; No. 868). doi: 10.1007/978-3-030-01054-6_71