Representatives for Visually Analyzing Cluster Hierarchies
Stefan Brecheisen, Hans‐Peter Kriegel, Martin Pfeifle · 2003
Similarity search in database systems is becoming an in-creasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, computer aided engineering, marketing and purchasing as-sistance as well as many others. In this paper, we show how visualizing the hierarchical clustering structure of a database of objects can aid the user in his time consum-ing task to find similar objects. We present related work and explain its shortcomings which led to the development of our new methods. Based on reachability plots, we intro-duce approaches which automatically extract the significant clusters in a hierarchical cluster representation along with suitable cluster representatives. These techniques can be used as a basis for visual data mining. We implemented our algorithms resulting in an industrial prototype which we used for the experimental evaluation. This evaluation is based on a real world test data set and points out that our new approaches to automatic cluster recognition and extrac-tion of cluster representatives create meaningful and useful results. 1.