An Experimental Platform Integrating Variety Clustering Algorithms with Related Techniques
The clustering analysis techniques have been widely applied in many fields and many clustering algorithms emerge with specific drawbacks and merits. However, the popular data mining tools do not reflect the upto-date research result in clustering and cannot satisfy the application requests. Therefore, the paper proposes an experimental platform, which combines the new clustering techniques with outlier detection techniques, dimensionality reduction technique and visualization technique, and the platform is also applied in the many fields, such as 3D model retrieval. After stating the structure of the platform, the paper introduces its performances.
Clustering outlier detection dimensionality reduction visualization
Xizhe Zhang
College of Information Science and Engineering Northeastern University Shenyang, China
国际会议
桂林
英文
478-481
2010-11-17（万方平台首次上网日期，不代表论文的发表时间）