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UPDis: A user-assisted projection technique for distance information

机译：UPDis：一种用于距离信息的用户辅助投影技术

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摘要

Multidimensional projection techniques have become essential analytical tools. Typically, they map data from a high-dimensional space into a low-dimensional visual space, preserving distance or neighborhood structures on the produced layout. Despite the advances, with faster and highly precise techniques, existing methods still carry deficiencies that impair their use as exploratory tools. An example is the mismatching that can occur between what the user considers similar/dissimilar and what is conveyed by the visual representation. Recently, a class of projection techniques aims at addressing this limitation, allowing users to control the projection process by changing the distance relationships using small data samples. Among such methods, Local Affine Multidimensional Projection has proved to be the state-of-the-art regarding the effectiveness of user intervention. Although Local Affine Multidimensional Projection has attained a relative success, it is limited to certain application domains. Since it relies on feature vector representations with data instances described by vectors embedded into a Euclidean space, scenarios that offer only distance information or a distance function cannot be handled. In this article, we present a novel multidimensional projection technique, called User-assisted Projection Technique for Distance Information, which takes advantage of the solid mathematical framework provided by Local Affine Multidimensional Projection, adapting it to scenarios where only distance information or a distance function is available. The results show that User-assisted Projection Technique for Distance Information is as fast, accurate, robust, and flexible as the existing state-of-the-art techniques, enabling the application of the refined user control provided by Local Affine Multidimensional Projection on domains not previously covered. Its versatility is illustrated in an application that involves the organization of book collections that employs an external source of information for the recommendation of new readings.
机译：多维投影技术已成为必不可少的分析工具。通常，它们将数据从高维空间映射到低维视觉空间，从而在生成的布局上保留距离或邻域结构。尽管取得了进步，但借助更快，更精确的技术，现有方法仍然存在一些缺陷，从而削弱了它们作为探索工具的使用。一个示例是用户认为相似/不相似的内容与视觉表示所传达的内容之间可能发生的不匹配。最近，一类投影技术旨在解决这一局限性，允许用户使用小数据样本通过更改距离关系来控制投影过程。在这些方法中，本地仿射多维投影已被证明是有关用户干预效果的最新技术。尽管局部仿射多维投影取得了相对成功，但仅限于某些应用程序域。由于它依赖于特征向量表示，其数据实例由嵌入到欧氏空间中的向量描述，因此无法处理仅提供距离信息或距离函数的方案。在本文中，我们提出了一种新颖的多维投影技术，称为距离信息的用户辅助投影技术，该技术利用了本地仿射多维投影提供的可靠数学框架，将其适应于仅距离信息或距离函数为可用。结果表明，距离信息的用户辅助投影技术与现有的最新技术一样快速，准确，健壮和灵活，从而可以将本地仿射多维投影提供的改进的用户控件应用于域以前没有涵盖。在一个涉及书籍收藏组织的应用程序中说明了它的多功能性，该组织使用外部信息源来推荐新的阅读材料。

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