基于焦点的多尺度可视化聚类

François Boutin, Mountaz Hascoët
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引用次数: 7

摘要

以前在导航历史可视化方面的工作为用户提供了一个概览,方便检索已经访问过的页面。这些技术大多依赖于导航树的构造,而不考虑底层超文本图的结构。因此,这些视图在很大程度上依赖于访问页面的顺序。在大多数情况下,它们仅限于一个会话,并且不容易表示大量页面集合。我们提出了一种基于[L。Tauscher et al.,(1997)]。基于底层超文本图的结构。我们的目标是使用这种方法将访问过的页面自动组织成一个层次聚类图,以提供多个会话期间访问过的页面的多尺度可视化。我们对导航历史的初步实验很有希望。我们相信我们的聚类方法足够通用,可以应用于具有底层高连接图结构的其他数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Focus-based clustering for multiscale visualization
Previous works on the visualization of navigation history has provided users with overviews that facilitate the retrieval of already visited pages. Most of these techniques rely on the construction of a navigation tree without accounting much for the structure of the underlying hypertext graph. Therefore such views are heavily dependent on the order of page visited. In most cases, they are limited to one session and cannot easily represent large collections of pages. We propose a clustering method based [L. Tauscher et al., (1997)] on a focus [M. Hascoet] on the structure of the underlying hypertext graph. Our aim is to use this method to automatically organize visited pages into a hierarchically clustered graph to provide multiscale visualization of pages visited during several sessions. Our initial experiments with navigation history are promising. We believe that our clustering method is general enough to be applied to other data with an underlying highly connected graph structure.
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