Similarity search in database systems is becoming an increasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, computer aided engineering, marketing and purchasing assistance 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 consuming 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 introduce approaches which automatically extract the significant clusters in a hierarchical cluster representation along with suitable cluster representatives. Thes
Due to the technological progress over the last decades, today’s scientific and commercial applicati...
Nowadays, the representation of many real word problems needs to use some type of relational model. ...
Fig. 1. Hierarchical clustering results on a synthetic point dataset (the black dots) are shown as a...
Similarity search in database systems is becoming an increasingly important task in modern applicati...
Similarity search in database systems is becoming an in-creasingly important task in modern applicat...
Similarity search in database systems is becoming an increas-ingly important task in modern applicat...
Hierarchical clustering algorithms are typically more effective in detecting the true clustering str...
Hierarchical clustering is very versatile in real world applications. However, due to the issue of h...
Introduction In the last ten years, an increasing number of database applications has emerged for w...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
With the much increased capability of data collection and storage in the past decade, data miners ha...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
In this paper, we present a methodology on how to measure the visual similarity between a query imag...
Structured and semi-structured object representations are getting more and more important for moder...
AbstractIn this work the topic of applying clustering as a knowledge extraction method from real-wor...
Due to the technological progress over the last decades, today’s scientific and commercial applicati...
Nowadays, the representation of many real word problems needs to use some type of relational model. ...
Fig. 1. Hierarchical clustering results on a synthetic point dataset (the black dots) are shown as a...
Similarity search in database systems is becoming an increasingly important task in modern applicati...
Similarity search in database systems is becoming an in-creasingly important task in modern applicat...
Similarity search in database systems is becoming an increas-ingly important task in modern applicat...
Hierarchical clustering algorithms are typically more effective in detecting the true clustering str...
Hierarchical clustering is very versatile in real world applications. However, due to the issue of h...
Introduction In the last ten years, an increasing number of database applications has emerged for w...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
With the much increased capability of data collection and storage in the past decade, data miners ha...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
In this paper, we present a methodology on how to measure the visual similarity between a query imag...
Structured and semi-structured object representations are getting more and more important for moder...
AbstractIn this work the topic of applying clustering as a knowledge extraction method from real-wor...
Due to the technological progress over the last decades, today’s scientific and commercial applicati...
Nowadays, the representation of many real word problems needs to use some type of relational model. ...
Fig. 1. Hierarchical clustering results on a synthetic point dataset (the black dots) are shown as a...