processes with graphic visualization, penalizes both procedures with each other's
deficiencies and limitations. For example, because an analytical process can't analyze …

Visual Data Mining—Opening the Black Box Knowledge discovery holds the promise of
insight into large, otherwise opaque datasets. Thenatureofwhatmakesaruleinterestingtoau …

The visual senses for humans have a unique status, offering a very broadband channel for
information flow. Visual approaches to analysis and mining attempt to take advantage of our …

In many application domains, data is collected and referenced by its geo-spatial location.
Spatial data mining, or the discovery of interesting patterns in such databases, is an …

Never before in history has data been generated at such high volumes as it is today.
Exploring and analyzing the vast volumes of data is becoming increasingly difficult …

We are living in a world which faces a rapidly increasing amount of data to be dealt with on a
daily basis. In the last decade, the steady improvement of data storage devices and means …

Never before in history has data been generated at such high volumes as it is today.
Exploring and analyzing the vast volumes of data has become increasingly difficult …

Never before in history data has been generated and collected in such high volumes as it is
today. Keeping up to date with the flood of data, using standard tools for data analysis and …

Goals of Visualization Techniques u Explorative Analysis• starting point: data without
hypotheses about the data• process: interactive, usually undirected search for structures …

We survey work on the different uses of graphical mapping and interaction techniques for
visual data mining of large data sets represented as table data. Basic terminology related to …