Visual analytics for massive multivariate networks

大规模多元网络的可视化分析

• 批准号: LP160100935
• 负责人: Prof Seok-Hee Hong
• 金额: $ 26.54万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2017
• 资助国家: 澳大利亚
• 起止时间: 2017-06-15 至 2022-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP160100935
• 关键词: Visual; analytics; massive; multivariate; networks

Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.

大规模多变量网络的可视化分析。该项目旨在创建可视化分析大规模多元网络的方法。近年来，可用的网络数据量呈爆炸式增长：软件系统、社交网络和生物系统拥有数百万个节点和数十亿条具有多元属性的边。它们的规模和复杂性使得这些数据集难以利用。需要更有效的方法来理解数据。该项目将设计，实现和评估大量多元网络数据集的可视化方法。这项研究预计将被澳大利亚的软件开发、生物技术和安全公司用来利用他们的数据。