Modelling and Searching Cohesive Groups over Heterogeneous Graphs

在异构图上建模和搜索内聚群

• 批准号: DP220102191
• 负责人: Prof Chengfei Liu
• 金额: $ 29.91万
• 依托单位: Swinburne University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2022
• 资助国家: 澳大利亚
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP220102191
• 关键词: Modelling; Searching; Cohesive; Groups; over

Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for different applications and devise efficient algorithms for searching and monitoring those cohesive groups based on different models. The methods, techniques, and evaluation systems developed in this project can be deployed to facilitate the smart use of heterogeneous information networks across the nation.

异构信息网络（HIN）包含更丰富的结构和语义信息，这些信息表示为不同类型的对象和链接。从HIN中搜索内聚群体发现了许多应用，也带来了概念和技术层面的挑战。该项目旨在研究有效的建模的内聚群体，考虑到同质和异构的信息，为不同的应用程序和设计有效的算法，搜索和监测这些内聚群体的基础上不同的模型。在这个项目中开发的方法，技术和评估系统可以部署，以促进全国各地的异构信息网络的智能使用。