HD-Eye - Visual Clustering of High dimensional Data

Clustering of large data bases is an important research area with a large variety of applications in the data base context. Missing in most of the research efforts are means for guiding the clustering process and understanding the results, which is especially important for high dimensional data. Visualization technology may help to solve this problem since it provides effective support of different clustering paradigms and allows a visual inspection of the results. The HD-Eye (high-dim. eye) system shows that a tight integration of advanced clustering algorithms and state-of-the-art visualization techniques is powerful for a better understanding and effective guidance of the clustering process, and therefore can help to significantly improve the clustering results. Clustering High Dimensional Data Clustering in large databases of high-dimensional data is an interesting and important, but difficult problem. The clustering problem may be defined as the problem of partitioning the set of...

• Type: Conference
• Year: 2003
• Where: ICDE
• Authors: Alexander Hinneburg, Daniel A. Keim, Markus Wawryniuk
• Keywords: Clustering Algorithms, Clustering Process, Database, Dimensional Data Clustering, ICDE 2003