Taming Large-Volume Dynamic Graphs in the Cloud

该项目旨在开发高效、可扩展的算法来处理云中的大容量动态图形。该项目希望在大容量动态图形处理方面解决关键挑战并奠定理论基础，这在开发通用的、实时的结构化搜索引擎方面发挥着重要作用。该项目的预期结果包括处理随时间快速发展的大图形的理论基础和可扩展算法。这使用户能够实时监控和分析大型动态网络中的结构信息。该项目有望为图形处理开辟新的研究方向，丰富前沿技术，惠及澳大利亚的许多关键应用。

This project aims to develop efficient and scalable algorithms to process large-volume dynamic graphs in the cloud. The project expects to address key challenges and lay theoretical foundations in large-volume dynamic graph processing, which plays an important role in developing general-purpose, real-time structural search engines. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big graphs that evolve rapidly over time. These enable users to monitor and analyse structural information in large dynamic networks in real time. The project expects to open up a new research direction for graph processing to enrich frontier technologies and benefit many key applications in Australia.