Modelling and Searching Cohesive Groups over Heterogeneous Graphs

异质信息网络(HIN)包含更丰富的结构和语义信息，表示为不同类型的对象和链接。从HINS中搜索有凝聚力的群体发现了许多应用，但也带来了概念和技术层面的挑战。该项目的目的是研究针对不同应用同时考虑同质和异质信息的凝聚群的有效建模，并设计基于不同模型的高效算法来搜索和监控这些凝聚群。该项目开发的方法、技术和评估系统可以用于促进全国范围内的异质信息网络的智能使用。

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.