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Visual-Spatial Exploration of Thematic Spaces: A Comparative Study of Three Visualisation Models

机译:专题空间的视觉空间探索:三种可视化模型的比较研究

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Scatter graphs (e.g. SPIRE Galaxies, Bead, VR-VIBE) are a popular medium for visualising spatial-semantic structures derived from abstract information spaces. For small spaces (i.e. less than one hundred nodes), such graphs can be an effective means of reducing high-dimensional information into two or three spatial dimensions. As dimensionality increases, representing the thematic diversity of documents using spatial proximity alone becomes less and less effective. This paper reports an experiment designed to determine whether, for larger spaces, benefits are to be gained from adding visual links between document nodes as an additional means of representing the most important semantic relationships. Two well known algorithms, minimum spanning trees (MST) and pathfinder associative networks (PFNET), were tested against both a scatter graph visualisation, derived from factor analysis, and a traditional list-based hypertext interface. It was hypothesised that visual links would facilitate users' comprehension of the information space with corresponding gains in information seeking performance. Navigation performance and user impressions were analysed across a range of different search tasks. Results indicate both significant performance gains and more positive user feedback for MST and PFNET visualisations over scatter graphs. Performance on all visualisations was generally poorer and never better than that achieved on the text list interface, although the magnitude of these differences was found to be highly task dependent.
机译:散射图(例如尖顶星系,珠,VR-Vibe)是一种流行的介质,用于可视化从抽象信息空间衍生的空间语义结构。对于小空间(即,百分比节点),这样的图可以是将高维信息降至两三个空间尺寸的有效手段。随着维度的增加,代表单独使用空间邻近的文件的主题多样性变得越来越少。本文报告了一个实验,设计用于确定较大的空间,从文档节点之间添加可视链接作为代表最重要的语义关系的额外方法。测试两个众所周知的算法,最小的生成树(MST)和Pathfinder关联网络(PFNet),用于源自因子分析的散点图,以及传统的基于列表的超文本接口。假设视觉链接将促进用户在寻求表现的信息中具有相应的收益来理解信息空间。在一系列不同的搜索任务中分析导航性能和用户印象。结果表明散射图中MST和PFNET可视化的显着性能增益和更积极的用户反馈。所有可视化的性能通常较差,而不是比文本列表界面所达到的更差,尽管发现这些差异的大小依赖于高度任务。

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