VISHIEN-MAAT: Scrollytelling visualization design for explaining Siamese Neural Network concept to non-technical users

IF 3.8 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Visual Informatics Pub Date : 2023-03-01 DOI:10.1016/j.visinf.2023.01.004
Noptanit Chotisarn , Sarun Gulyanon , Tianye Zhang , Wei Chen
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引用次数: 1

Abstract

The past decade has witnessed rapid progress in AI research since the breakthrough in deep learning. AI technology has been applied in almost every field; therefore, technical and non-technical end-users must understand these technologies to exploit them. However existing materials are designed for experts, but non-technical users need appealing materials that deliver complex ideas in easy-to-follow steps. One notable tool that fits such a profile is scrollytelling, an approach to storytelling that provides readers with a natural and rich experience at the reader’s pace, along with in-depth interactive explanations of complex concepts. Hence, this work proposes a novel visualization design for creating a scrollytelling that can effectively explain an AI concept to non-technical users. As a demonstration of our design, we created a scrollytelling to explain the Siamese Neural Network for the visual similarity matching problem. Our approach helps create a visualization valuable for a short-timeline situation like a sales pitch. The results show that the visualization based on our novel design helps improve non-technical users’ perception and machine learning concept knowledge acquisition compared to traditional materials like online articles.

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VISHIEN-MAAT:用于向非技术用户解释暹罗神经网络概念的滚动可视化设计
自深度学习取得突破以来,过去十年人工智能研究取得了快速进展。人工智能技术几乎已应用于各个领域;因此,技术和非技术的最终用户必须了解这些技术才能加以利用。然而,现有的材料是为专家设计的,但非技术用户需要有吸引力的材料,以易于遵循的步骤提供复杂的想法。适合这种简介的一个值得注意的工具是滚动滚动,这是一种讲故事的方法,可以按照读者的节奏为读者提供自然而丰富的体验,以及对复杂概念的深入互动解释。因此,这项工作提出了一种新颖的可视化设计,用于创建滚动条,可以向非技术用户有效解释人工智能概念。作为我们设计的一个演示,我们创建了一个滚动条来解释暹罗神经网络在视觉相似性匹配问题上的作用。我们的方法有助于创建一个对销售推介等短时间情况有价值的可视化。结果表明,与在线文章等传统材料相比,基于我们新颖设计的可视化有助于提高非技术用户的感知和机器学习概念知识的获取。
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来源期刊
Visual Informatics
Visual Informatics Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
6.70
自引率
3.30%
发文量
33
审稿时长
79 days
期刊最新文献
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