Towards Processing of Big Streaming Temporal Graphs

面向大流时态图的处理

• 批准号: DE240100668
• 负责人: Dr Dong Wen
• 金额: $ 30.12万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE240100668
• 关键词: Towards; Processing; Big; Streaming; Temporal

This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big streaming temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and social analysis.

该项目旨在开发高效和可扩展的算法来处理大型流式时间图，这对于许多数据密集型应用（如网络安全，犯罪监控和电子营销）具有很高的需求。特别是，我将研究三种最具代表性的查询类型，包括基于顶点的查询，基于路径的查询和基于子图的查询。本项目的预期成果包括理论基础和可扩展的算法来处理大的流时间图，以及一个系统原型的评估和展示的实用价值。该项目的成功将为许多重要的应用程序带来重大利益，如网络安全，电子商务，健康和社会分析。