TBSSvis：面向时间盲源分离的可视化分析
TBSSvis: Visual Analytics for Temporal Blind Source Separation
AI总结：
本文针对时间盲源分离分析工具交互不足和参数空间考虑不充分的问题，提出基于可视化分析的设计研究和交互式Web原型TBSSvis，并通过专家访谈验证其能有效支持TBSS结果分析工作流程。
摘要：
时间盲源分离（TBSS）用于从含噪的时间多变量数据（如心电图）中获取真实的潜在过程。TBSS与主成分分析（PCA）有相似之处，它将输入数据分离为单变量成分，并适用于来自医学、金融或土木工程等多个领域的合适数据集。尽管TBSS具有广泛的适用性，但当前工具对其涉及的任务支持不足，仅提供基于文本的交互和单一静态图像。分析人员在分析和比较所获得的结果时受到限制，这些结果包含矩阵和时间序列集合等多种数据。此外，参数设置对分离性能有很大影响，但由于工具不当，分析人员目前并未考虑整个参数空间。我们提出通过应用可视化分析（VA）原则来解决这些问题。我们的主要贡献是一项针对TBSS的设计研究，迄今为止可视化社区尚未对此进行探索。我们在以用户为中心的设计过程中开发了任务抽象和可视化设计。我们的次要贡献是针对具体任务组装成熟的可视化技术和算法，以深入理解TBSS过程。我们提出了TBSSvis，一个基于Web的交互式VA原型，并在与五位TBSS专家的两次访谈中对其进行了广泛评估。这些访谈的反馈和观察表明，TBSSvis支持实际工作流程，并且交互式可视化的组合有助于完成分析TBSS结果所涉及的任务。
英文摘要：
Temporal Blind Source Separation (TBSS) is used to obtain the true underlying processes from noisy temporal multivariate data, such as electrocardiograms. TBSS has similarities to Principal Component Analysis (PCA) as it separates the input data into univariate components and is applicable to suitable datasets from various domains, such as medicine, finance, or civil engineering. Despite TBSS's broad applicability, the involved tasks are not well supported in current tools, which offer only text-based interactions and single static images. Analysts are limited in analyzing and comparing obtained results, which consist of diverse data such as matrices and sets of time series. Additionally, parameter settings have a big impact on separation performance, but as a consequence of improper tooling, analysts currently do not consider the whole parameter space. We propose to solve these problems by applying visual analytics (VA) principles. Our primary contribution is a design study for TBSS, which so far has not been explored by the visualization community. We developed a task abstraction and visualization design in a user-centered design process. Task-specific assembling of well-established visualization techniques and algorithms to gain insights in the TBSS processes is our secondary contribution. We present TBSSvis, an interactive web-based VA prototype, which we evaluated extensively in two interviews with five TBSS experts. Feedback and observations from these interviews show that TBSSvis supports the actual workflow and combination of interactive visualizations that facilitate the tasks involved in analyzing TBSS results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
