A study on applying KFCM algorithm to source code mining
Yonghui Liu, Jingjing Tian, Lei Zhang
Available Online November 2012.
- https://doi.org/10.2991/citcs.2012.118How to use a DOI?
- C-means;KFCMalgorithm;source code mining
- 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
- 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 -