AgentVis: Visual Analysis of Agent Behavior With Hierarchical Glyphs
AgentVis: Visual Analysis of Agent Behavior With Hierarchical Glyphs
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AgentVis：使用分层字形对代理行为进行可视化分析
DOI：
10.1109/tvcg.2020.2985923
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发表时间：
2020
影响因子：
5.2
通讯作者：
Aslam Miah
中科院分区：
文献类型：
--
作者：
Dylan Rees;R. Laramee;P. Brookes;Tony D'Cruze;G. A. Smith;Aslam Miah
表示复杂行为的符号提供了一种有用且通用的多变量数据可视化方法。然而，由于其复杂的形状，重叠和咬合的象形文字是一个普遍和突出的限制。这限制了可以在给定图像中显示的离散数据元组的数量。使用实际应用程序，字形用于描述呼叫中心中的座席行为。然而，许多呼叫中心都有成千上万的座席。用字形表示数千个代理的标准方法无法扩展。为了适应包含数千个字形的可视化，我们将重叠的字形聚类开发为单个父字形。此分层字形表示所有子代理字形的平均值，从而消除重叠并减少视觉混乱。与呼叫中心行业的领域专家合作，探索和开发了多变量聚类技术。我们根据缩放级别和自定义距离度量实现对字形簇的动态控制，以减少过度绘图和杂乱利用图像空间。我们通过示例和使用场景展示了我们的技术，使用真实世界的呼叫中心数据来可视化数千个呼叫中心座席，揭示对他们行为的洞察，并报告来自呼叫中心专家分析师的反馈。
Glyphs representing complex behavior provide a useful and common means of visualizing multivariate data. However, due to their complex shape, overlapping, and occlusion of glyphs is a common and prominent limitation. This limits the number of discreet data tuples that can be displayed in a given image. Using a real-world application, glyphs are used to depict agent behavior in a call center. However, many call centers feature thousands of agents. A standard approach representing thousands of agents with glyphs does not scale. To accommodate the visualization incorporating thousands of glyphs we develop clustering of overlapping glyphs into a single parent glyph. This hierarchical glyph represents the mean value of all child agent glyphs, removing overlap and reduTcing visual clutter. Multi-variate clustering techniques are explored and developed in collaboration with domain experts in the call center industry. We implement dynamic control of glyph clusters according to zoom level and customized distance metrics, to utilize image space with reduced overplotting and cluttering. We demonstrate our technique with examples and a usage scenario using real-world call-center data to visualize thousands of call center agents, revealing insight into their behavior and reporting feedback from expert call-center analysts.
影响因子：
2.3
作者：
Chung, David H. S.;Legg, Philip A.;Chen, Min
通讯作者：
Chen, Min
DOI：
10.1109/tvcg.2016.2640960
发表时间：
2017-03-01
影响因子：
5.2
作者：
Liu, Shusen;Maljovec, Dan;Pascucci, Valerio
通讯作者：
Pascucci, Valerio