Various graphs such as web or social networks may contain up to trillions of edges.
Compressing such datasets can accelerate graph processing by reducing the amount of I/O …

We propose Slim Graph: the first programming model and framework for practical lossy
graph compression that facilitates high-performance approximate graph processing …

Abstract We propose Diffusion Centrality (DC) in which semantic aspects of a social network
are used to characterize vertices that are influential in diffusing a property p. In contrast to …

Computations on irregular graph structures are important for many fields, including social
sciences, bioinformatics, chemistry, medicine, cybersecurity, healthcare, web graph …

Many real-world networks are large, complex and thus hard to understand, analyze or
visualize. Data about networks are not always complete, their structure may be hidden, or …

Semantic mining is a research area that sprung up in the last decade. With the explosively
growth of Linked Data, instance-focused Semantic Mining technologies now face the …

The network backbone is a reduced but meaningful representation of dense complex
network, which is helpful to understand the topological characteristics and grasp the key …

图聚集技术旨在获取能够涵盖原图大部分信息的简洁超图, 用于提炼概要信息,
解决存储消耗和社交隐私保护等问题. 对当前的图聚集技术进行研究, 综述了现有图聚集技术中 …

Purpose: With the availability and utilization of Inter-Country Input-Output (ICIO) tables, it is
possible to construct quantitative indices to assess its impact on the Global Value Chain …

图聚集技术旨在获取能够涵盖原图大部分信息的简洁超图, 用于提炼概要信息,
解决存储消耗和社交隐私保护等问题. 对当前的图聚集技术进行研究, 综述了现有图聚集技术中 …