Information visualization and visual data mining
Information visualization and visual data mining
复制标题
DOI：
10.1109/2945.981847
复制
发表时间：
2002-01-01
影响因子：
5.2
通讯作者：
Keim, DA
中科院分区：
文献类型：
--
作者：
Keim, DA
历史上从来没有像今天这样产生如此高的数据量。探索和分析海量数据变得越来越困难。信息可视化和可视化数据挖掘有助于处理海量信息。可视化数据探索的优势在于用户可以直接参与到数据挖掘过程中。在过去的十年中，为了支持对大数据集的探索，已经开发了大量的信息可视化技术。本文提出了一种信息可视化和可视化数据挖掘技术的分类方法，该分类方法基于要可视化的数据类型、可视化技术和交互与失真技术。我们使用几个示例来说明分类，其中大多数涉及本特殊部分中介绍的技术和系统。
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. Information visualization and visual data mining can help to deal with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data mining process. There are a large number of information visualization techniques which have been developed over the last decade to support the exploration of large data sets. In this paper, we propose a classification of information visualization and visual data mining techniques which is based on the data type to be visualized, the visualization technique, and the interaction and distortion technique. We exemplify the classification using a few examples, most of them referring to techniques and systems presented in this special section.