Add to ORKGThis paper describes a cluster visualization system used for data-mining fraud detection. The system can simultaneously show 6 dimensions of data, and a unique technique of 3D nonlinear magnification allows individual clusters of data points to be magnified while still maintaining a view of the global context. The author first describes the fraud detection problem, along with the data which is to be visualized. Then he describes general characteristics of the visualization system, and shows how nonlinear magnification can be used in this system. Finally he concludes and describes options for further work
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being ...
Due to the technological progress over the last decades, today’s scientific and commercial applicati...
One of the most important tasks in modern world is to find solutions to problems of processing and a...
Abstract — In this paper, we re-consider the problem of mapping a high-dimensional data set into a l...
Cluster analysis is an important technique that has been used in data mining. However, cluster analy...
The visual exploration of large databases raises a number of unresolved inference problems and calls...
Today there are abounding collected data in cases of various diseases in medical sciences. Physician...
Visual data mining techniques have proven to be of high value in exploratory data analysis and they ...
Evaluation of clustering partitions is a crucial step in data processing. A multitude of measures ex...
Abstract-Visual data mining techniques have proven to be of high value in exploratory data analysis,...
Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to...
With the much increased capability of data collection and storage in the past decade, data miners ha...
Clustering is a powerful analysis technique used to detect structures in data sets. The output of a...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being ...
Due to the technological progress over the last decades, today’s scientific and commercial applicati...
One of the most important tasks in modern world is to find solutions to problems of processing and a...
Abstract — In this paper, we re-consider the problem of mapping a high-dimensional data set into a l...
Cluster analysis is an important technique that has been used in data mining. However, cluster analy...
The visual exploration of large databases raises a number of unresolved inference problems and calls...
Today there are abounding collected data in cases of various diseases in medical sciences. Physician...
Visual data mining techniques have proven to be of high value in exploratory data analysis and they ...
Evaluation of clustering partitions is a crucial step in data processing. A multitude of measures ex...
Abstract-Visual data mining techniques have proven to be of high value in exploratory data analysis,...
Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to...
With the much increased capability of data collection and storage in the past decade, data miners ha...
Clustering is a powerful analysis technique used to detect structures in data sets. The output of a...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being ...
Due to the technological progress over the last decades, today’s scientific and commercial applicati...