Modelling and Mining Complex Networks as Hypergraphs

将复杂网络建模和挖掘为超图

• 批准号: 577565-2022
• 负责人: Pralat, PawelPA
• 金额: $ 7.07万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758455
• 关键词: Modelling; Mining; Complex; Networks; Hypergraphs

Hypergraphs have recently emerged as a useful representation for complex networks since they allow capturing more general relations than graphs. Research on the generalization of various graph-based tools and techniques is booming and, in parallel, new software packages are being developed. Having said that, the theory and tools are still not sufficiently developed to allow most problems to be tackled directly within this context. Hypergraphs are of particular interest in the field of knowledge discovery where most problems currently modelled as graphs would be more accurately modelled as hypergraphs. Those in the knowledge discovery field are particularly interested in the generalization of the concepts of modularity and diffusion to hypergraphs. Such generalizations require a firm theoretical base on which to develop these concepts. Unfortunately, although hypergraphs were formally defined in the 1960s (and various realizations of hypergraphs were studied long before that), the general formal theory is not as mature as required for the applications of interest to practitioners. The main goal of this collaboration is to develop formal theory, in conjunction with development of concrete applications. Given that different research groups in various parts of the world have recently started pursuing results in this direction, the proposal seems particularly well-timed as an occasion for the cross-pollination of research directions, the establishment of new collaborations and the exchange of tools and techniques.

超图最近已经成为复杂网络的一种有用的表示，因为它们允许捕获比图更一般的关系。对各种基于图形的工具和技术的推广的研究正在蓬勃发展，同时，新的软件包正在开发中。话虽如此，理论和工具仍然不够发达，不能在这种背景下直接解决大多数问题。超图在知识发现领域特别令人感兴趣，目前建模为图的大多数问题都会更准确地建模为超图。知识发现领域的人特别感兴趣的是将模块化和扩散的概念推广到超图上。这样的概括需要坚实的理论基础来发展这些概念。不幸的是，虽然超图在20世纪60年代被正式定义(在此之前很久人们就研究了超图的各种实现)，但一般的形式理论并不像实践者感兴趣的应用所需的那样成熟。这种合作的主要目标是开发形式理论，以及开发具体的应用程序。鉴于世界各地的不同研究小组最近开始追求这方面的成果，该提案似乎特别适时，可作为交叉授粉研究方向、建立新的合作以及交流工具和技术的机会。