文章基本信息

标题：Evolutionary Computation for Label Layout on Unused Space of Stacked Graphs
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作者：Alejandro Toledo ; Kingkarn Sookhanaphibarn ; Ruck Thawonmas 等
期刊名称：ISRN Artificial Intelligence
印刷版ISSN：2090-7435
电子版ISSN：2090-7443
出版年度：2012
卷号：2012
DOI：10.5402/2012/139603
出版社：Hindawi Publishing Corporation
摘要：Placing numerous objects and their corresponding labels in the stacked graph visualization is a challenging problem. In the stacked graph, different combinations of initial parameters and filtering effects yield views with hidden information, illegible labels, and unused space. The result is a tool that does not take advantage on the unused space to reveal information to the user for further investigation. We present an automatic method for label layout on the unused space in a stacked graph. An evolutionary computation (EC) is used to optimize the best label position according to legibility requirements, as well as requirements for keeping semantic relationships between labels and their representative visual objects. A number of EC experiments, as well as a usability study on label legibility, show that our proposed solution looks promising, as compared to the traditional solutions.