Clustering technique in data mining : general and research perspective.

As the amount and dimensionality of data grows beyond the grasp of human minds, automation of pattern discovery becomes crucial. One of the most popular techniques to extract pattern and knowledge from large amount of data in databases is data mining. Data mining can be defined as process of searchi...

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Main Authors: Che Mat @ Mohd. Shukor, Zamzarina, Md. Sap, Mohd. Noor
Format: Article
Language:English
Published: Penerbit UTM Press 2002
Subjects:
Online Access:http://eprints.utm.my/8550/1/ZamzarinaCheMat2002_ClusteringTechniqueInDataMining.PDF
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author Che Mat @ Mohd. Shukor, Zamzarina
Md. Sap, Mohd. Noor
author_facet Che Mat @ Mohd. Shukor, Zamzarina
Md. Sap, Mohd. Noor
author_sort Che Mat @ Mohd. Shukor, Zamzarina
collection ePrints
description As the amount and dimensionality of data grows beyond the grasp of human minds, automation of pattern discovery becomes crucial. One of the most popular techniques to extract pattern and knowledge from large amount of data in databases is data mining. Data mining can be defined as process of searching the particular patterns and relationship from large amount of data in databases using sophisticated data analysis tools and techniques to build models that may be used to make valid predictions. One of the existing data mining techniques is clustering. Clustering in data mining is a discovery process that groups a set of data such that the intra-cluster similarity is maximized and inter-cluster similarity is minimizes. These discovered clusters are used to explain the characteristics of the data distribution. This paper present most popular clustering technique such as hierarchical clustering and partitional clustering, cluster selection schemes, clustering criterion functions, assessing cluster quality and conclusion.
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spelling utm.eprints-85502017-11-01T04:17:42Z http://eprints.utm.my/8550/ Clustering technique in data mining : general and research perspective. Che Mat @ Mohd. Shukor, Zamzarina Md. Sap, Mohd. Noor QA75 Electronic computers. Computer science As the amount and dimensionality of data grows beyond the grasp of human minds, automation of pattern discovery becomes crucial. One of the most popular techniques to extract pattern and knowledge from large amount of data in databases is data mining. Data mining can be defined as process of searching the particular patterns and relationship from large amount of data in databases using sophisticated data analysis tools and techniques to build models that may be used to make valid predictions. One of the existing data mining techniques is clustering. Clustering in data mining is a discovery process that groups a set of data such that the intra-cluster similarity is maximized and inter-cluster similarity is minimizes. These discovered clusters are used to explain the characteristics of the data distribution. This paper present most popular clustering technique such as hierarchical clustering and partitional clustering, cluster selection schemes, clustering criterion functions, assessing cluster quality and conclusion. Penerbit UTM Press 2002-12 Article PeerReviewed application/pdf en http://eprints.utm.my/8550/1/ZamzarinaCheMat2002_ClusteringTechniqueInDataMining.PDF Che Mat @ Mohd. Shukor, Zamzarina and Md. Sap, Mohd. Noor (2002) Clustering technique in data mining : general and research perspective. Jurnal Teknologi Maklumat, 14 (2). pp. 50-63. ISSN 0128-3790
spellingShingle QA75 Electronic computers. Computer science
Che Mat @ Mohd. Shukor, Zamzarina
Md. Sap, Mohd. Noor
Clustering technique in data mining : general and research perspective.
title Clustering technique in data mining : general and research perspective.
title_full Clustering technique in data mining : general and research perspective.
title_fullStr Clustering technique in data mining : general and research perspective.
title_full_unstemmed Clustering technique in data mining : general and research perspective.
title_short Clustering technique in data mining : general and research perspective.
title_sort clustering technique in data mining general and research perspective
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/8550/1/ZamzarinaCheMat2002_ClusteringTechniqueInDataMining.PDF
work_keys_str_mv AT chematmohdshukorzamzarina clusteringtechniqueindatamininggeneralandresearchperspective
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