A novel clustering algorithm based on weighted support and its application

被引：0
|
作者：
Yang, XR [1 ]
Shen, JY [1 ]
Liu, Q [1 ]
机构：
[1] Xi An Jiao Tong Univ, Dept Comp Sci & Technol, Xian 710049, Peoples R China
来源：
2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS | 2002年
关键词：
weighted support; clustering; categorical data; intrusion detection;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present a novel and efficient algorithm-WeiSC for clustering categorical data; it is not only accurate but also deserves good scalability. It is mainly based on weighted support, which defined by us, to calculate the similarity between a new tuple and existing clusters. The new tuple was assigned to the cluster with largest similarity. Proof show WeiSC to be reasonable, experimental results show WeiSC to be more accurate than some existed algorithm. As an instance, we apply this algorithm in IDS, and perform some research.
引用
收藏
页码：95 / 100
页数：6
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