使用视觉提示实现有效的树木探索

Q3 Computer Science
Quang Vinh Nguyen , David Arness , Carrissa J. Sanderson , Simeon Simoff , Mao Lin Huang
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引用次数: 1

摘要

本文提出了一种新的交互式可视化,通过在节点链接树可视化上提供视觉提示来探索大型层次结构。我们的技术提供了具有三种类型视觉提示的隐藏子结构的拓扑预览,包括简单提示、树提示和树图提示。我们在兴趣度树(DOITree)上展示了视觉线索,因为它熟悉的映射、提供多个聚焦节点的能力,以及它对子结构的动态重新缩放以适应可用空间。我们对28名参与者进行了一项可用性研究,测量了五项不同拓扑搜索任务的完成时间和准确性。在三个节点识别任务中,简单提示的完成时间最快。在五项任务中,有四项任务的树图线索的正确率最高,尽管其中两项任务的正确率仅达到统计学显著性。正如预测的那样,用户评分显示出对易于理解的树提示和简单提示的偏好,尽管这并没有一致地反映在性能结果中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enabling effective tree exploration using visual cues

This article presents a new interactive visualization for exploring large hierarchical structures by providing visual cues on a node link tree visualization. Our technique provides topological previews of hidden substructures with three types of visual cues including simple cues, tree cues and treemap cues. We demonstrate the visual cues on Degree-of-Interest Tree (DOITree) due to its familiar mapping, its capability of providing multiple focused nodes, and its dynamic rescaling of substructures to fit the available space. We conducted a usability study with 28 participants that measured completion time and accuracy across five different topology search tasks. The simple cues had the fastest completion time across three of the node identification tasks. The treemap cues had the highest rate of correct answers on four of the five tasks, although only reaching statistical significance for two of these. As predicted, user ratings demonstrated a preference for the easy to understand tree cues followed by the simple cue, despite this not consistently reflected in performance results.

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来源期刊
Journal of Visual Languages and Computing
Journal of Visual Languages and Computing 工程技术-计算机:软件工程
CiteScore
1.62
自引率
0.00%
发文量
0
审稿时长
26.8 weeks
期刊介绍: The Journal of Visual Languages and Computing is a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of visual languages and its implication to the art of computing. The journal publishes research papers, state-of-the-art surveys, and review articles in all aspects of visual languages.
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