FpVAT: a visual analytic tool for supporting frequent pattern mining
FpVAT: a visual analytic tool for supporting frequent pattern mining
复制标题
FpVAT：支持频繁模式挖掘的可视化分析工具
DOI：
10.1145/1809400.1809407
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Christopher L. Carmichael
中科院分区：
文献类型：
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作者：
C. Leung;Christopher L. Carmichael
由于频繁模式挖掘在许多知识发现和数据挖掘（KDD）任务中起着至关重要的作用，在过去的15年中，已经提出了许多发现频繁模式的算法。然而，大多数这些算法返回的挖掘结果的文本列表的形式包含频繁模式显示那些频繁出现的项目集。众所周知，“一图胜过千言万语”。使用视觉表示可以增强用户对频繁模式集合中的内在关系的理解。在本文中，我们开发了一个简单而有用的可视化分析工具，支持频繁模式挖掘称为FpVAT。这种可视化分析工具由两个模块组成：一个模块为用户提供概述，以便他们可以从大量的原始数据中获得洞察力;另一个模块使用户能够通过交互式可视化界面对挖掘结果进行分析推理，以便用户可以检测预期的频繁模式并发现意外的频繁模式。作为一个可视化分析工具，我们的FpVAT配备了几个交互式功能，为各种现实生活中的应用程序的数据分析和KDD过程提供有效的可视化支持。
As frequent pattern mining plays an essential role in many knowledge discovery and data mining (KDD) tasks, numerous algorithms for finding frequent patterns have been proposed over the past 15 years. However, most of these algorithms return the mining results in the form of textual lists containing frequent patterns showing those frequently occurring sets of items. It is well known that "a picture is worth a thousand words". The use of visual representation can enhance the user's understanding of the inherent relations in a collection of frequent patterns. In this paper, we develop a simple yet useful visual analytic tool for supporting frequent pattern mining called FpVAT. Such a visual analytic tool consists of two modules: One module gives users an overview so that they can derive insight from a massive amount of raw data; another module enables users to perform analytical reasoning on the mining results via interactive visual interfaces so that users can detect the expected frequent patterns and discover the unexpected frequent patterns. As a visual analytic tool, our FpVAT is equipped with several interactive features for effective visual support in the data analysis and KDD process for various real-life applications.