Proceedings of the 2012 National Conference on Information Technology and Computer Science

A study on applying KFCM algorithm to source code mining

Authors
Yonghui Liu, Jingjing Tian, Lei Zhang
Corresponding Author
Yonghui Liu
Available Online November 2012.
DOI
https://doi.org/10.2991/citcs.2012.118How to use a DOI?
Keywords
C-means;KFCMalgorithm;source code mining
Abstract
This paper provides a algorithm, which is based on that kernelized fuzzy C-means uses on the study of source code mining, to solve the problem that the large number of quantities, multiple attributes and most of them discrete of software engineering. By using this algorithm, we can improve the efficiency of mining and seek faster and more effective cluster approaches. Meanwhile, we can also solve the problem that the KFCM algorithm can not cluster text data directly. Then we can over the defect of only being able to obtain the minimum values by integrating KFCM and genetic algorithm. Finally, the experiment shows that the improved KFCM algorithm has a good clustering performance and high efficiency on data mining
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Proceedings
2012 National Conference on Information Technology and Computer Science
Part of series
Advances in Intelligent Systems Research
Publication Date
November 2012
ISBN
978-94-91216-39-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/citcs.2012.118How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yonghui Liu
AU  - Jingjing Tian
AU  - Lei Zhang
PY  - 2012/11
DA  - 2012/11
TI  - A study on applying KFCM algorithm to source code mining
BT  - 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 457
EP  - 459
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.118
DO  - https://doi.org/10.2991/citcs.2012.118
ID  - Liu2012/11
ER  -