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DCC : A framework for dynamic granular clustering
Peters, Georg Weber, Richard
Peters, Georg
Weber, Richard
Author
Abstract
Clustering is one of the most relevant data mining tasks. Its goal is to group similar objects in one cluster while dissimilar objects should belong to different clusters. Many extensions have been developed based on traditional cluster algorithms. Recently, approaches for dynamic as well as for granular clustering have been of particular interest. This paper provides a framework, DCC-Dynamic Clustering Cube, to categorize existing dynamic granular clustering algorithms. Furthermore, the DCC-Framework can be used as a research map and starting point for new developments in this area.
Keywords
dynamic clustering, granular clustering, granular computing
Date
2016
Type
Journal article
Journal
Granular Computing
Book
Volume
1
Issue
Page Range
1-11
Article Number
ACU Department
School of Arts and Humanities
Faculty of Education and Arts
Faculty of Education and Arts
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Relation URI
Source URL
Event URL
Open Access Status
License
All rights reserved
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Controlled