Visual analytics (VA) is a visually assisted exploratory analysis approach in which knowledge discovery is executed interactively between the user and system. The purpose of this study is to develop a method for the VA of set data aimed at supporting knowledge discovery and member selection. A typical target application is a visual support system for team analysis and member selection, by which users can analyze past teams and examine candidate lineups for new teams. Because there are several difficulties, such as the combinatorial explosion problem, developing a VA system of set data is challenging. In this study, we first define the requirements that the target system should satisfy and clarify the accompanying challenges. Then we propose a method for the VA of set data, which satisfies the requirements. The key idea is to model the generation process of sets and their outputs using a manifold network model. The proposed method visualizes the relevant factors as a set of topographic maps on which various information is visualized. Furthermore, using the topographic maps as a bidirectional interface, users can indicate their targets of interest in the system on these maps. We demonstrate the proposed method by applying it to basketball teams, showing how past teams are analyzed and how new lineups are examined. Because the method can be adapted to individual application cases by extending the network structure, it can be a general method by which practical systems can be built.
翻译:视觉分析(VA)是一种视觉辅助的探索性分析方法,在这种方法中,用户和系统之间互动地进行知识发现。本研究的目的是为VA开发一套旨在支持知识发现和成员选择的数据集数据的方法。一个典型的目标应用是团队分析和成员选择的视觉支持系统,用户可以通过这个系统分析过去的团队和检查新团队的候选阵列。由于存在若干困难,例如组合式爆炸问题,开发一个VA数据集系统具有挑战性。在这个研究中,我们首先界定目标系统应满足和澄清伴随的挑战的要求。然后我们提出一套符合要求的VA数据集数据的方法。关键的想法是利用一个多功能网络模型模拟成套数据集的生成过程及其输出。拟议方法将相关因素作为一组地形图的视觉化,以各种信息为基础。此外,使用地形图作为双向界面,用户可以表明他们对这些地图系统感兴趣的目标。我们通过将它应用到篮球队的方法演示了拟议的方法,以显示过去各组合是如何进行分析的,并且如何通过一个通用的系统来扩展整个系统的方法。