WebKIV: visualizing structure and navigation for Web mining applications

Yonghe Niu, Tong Zheng, Jiyang Chen, R. Goebel
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引用次数: 8

Abstract

A significant part of the Web mining problem is simply in understanding the value of any mining method. For example, the value of Web mining to improve user navigation is even more challenging if one can't visualize the differences over a large collection of Web pages or a significant structure within the existing Web. We present WebKIV, a tool we've developed to help us visualize our own results in Web mining. WebKIV combines strategies from several other Web visualization tools, to provide a single method of visualizing Web structure, and the results of Web mining on that structure. We summarize the value of Web visualization tools along the dimensions of scale (can one visualize small and large structures), navigation dynamics (can one visualize navigation dynamically or statically), and cumulative usage (can one distinguish individual and aggregate Web usage). We then show how WebKIV provides a way of visualizing the results of Web mining in a way that distinguishes properties along all three of these dimensions.
WebKIV: Web挖掘应用程序的可视化结构和导航
Web挖掘问题的一个重要部分就是理解任何挖掘方法的价值。例如,如果不能可视化大量Web页面或现有Web中的重要结构之间的差异,那么改进用户导航的Web挖掘的价值就更具挑战性了。我们将介绍WebKIV,这是我们开发的一个工具,可以帮助我们在Web挖掘中可视化我们自己的结果。WebKIV结合了来自其他几个Web可视化工具的策略,提供了一种可视化Web结构的方法,以及在该结构上进行Web挖掘的结果。我们总结了Web可视化工具在规模(可以可视化小型和大型结构)、导航动态(可以动态地或静态地可视化导航)和累积使用(可以区分单个和聚合Web使用)方面的价值。然后,我们将展示WebKIV如何提供一种将Web挖掘结果可视化的方法,这种方法可以区分这三个维度上的属性。
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