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http://hdl.handle.net/20.500.12358/24534
TitleA dynamic linkage clustering using KD-tree.
Untitled
Abstract

Some clustering algorithms calculate connectivity of each data point to its cluster by depending on density reachability. These algorithms can find arbitrarily shaped clusters, but they require parameters that are mostly sensitive to clustering performance. We develop a new dynamic linkage clustering algorithm using kd-tree. The proposed algorithm does not require any parameters and does not have a worst-case bound on running time that exists in many similar algorithms in the literature. Experimental results are shown in this paper to demonstrate the effectiveness of the proposed algorithm. We compare the proposed algorithm with other famous similar algorithm that is shown in literature. We present the proposed algorithm and its performance in detail along with promising avenues of future research.

Authors
Abudalfa, Shadi
Mikki, Mohammad
TypeJournal Article
Date2013
Subjects
dynamic linkage clustering
dbscan
data clustering
density-based clustering algorithm
kd-tree
Published inInt. Arab J. Inf. Technol.
SeriesVolume: 10, Number: 3
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  • Staff Publications- Faculty of Engineering [908]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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