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Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06)
A New k-means Based Clustering Algorithm in Aspect Mining
Timisoara, Romania
September 26-September 29
ISBN: 0-7695-2740-X
ASCII Text
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Gabriela Serban, Grigoreta Sofia Moldovan, "A New k-means Based Clustering Algorithm in Aspect Mining," Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on, pp. 69-74, Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06), 2006.
 
 
BibTex
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@article{ 10.1109/SYNASC.2006.5,
author = {Gabriela Serban and Grigoreta Sofia Moldovan},
title = {A New k-means Based Clustering Algorithm in Aspect Mining},
journal ={Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on},
volume = {0},
year = {2006},
isbn = {0-7695-2740-X},
pages = {69-74},
doi = {http://doi.ieeecomputersociety.org/10.1109/SYNASC.2006.5},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
TI - A New k-means Based Clustering Algorithm in Aspect Mining
SN - 0-7695-2740-X
SP69
EP74
A1 - Gabriela Serban,
A1 - Grigoreta Sofia Moldovan,
PY - 2006
KW - clustering
KW - aspect mining.
VL - 0
JA - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
ER -
 
Gabriela Serban, "Babes-Bolyai" University, Romania
Grigoreta Sofia Moldovan, "Babes-Bolyai" University, Romania
Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify cross-cutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming, in order to make them easier to maintain and to evolve.

This paper aims at presenting a new k-means based clustering algorithm used in Aspect Mining. Clustering is used in order to identify crosscutting concerns. We propose some quality measures in order to evaluate the results both from the clustering point of view and the aspect mining point of view, and we also report two case studies.

Index Terms:
clustering, aspect mining.
Citation:
Gabriela Serban, Grigoreta Sofia Moldovan, "A New k-means Based Clustering Algorithm in Aspect Mining," synasc, pp.69-74, Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06), 2006
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