Community structure in complex networks has been proven to be valuable in a variety of
fields, such as biology, social media, health, etc. Researchers have investigated a significant …

Understanding the evolving discipline of crime situations is a long-standing but significant
problem. Former methods prefer the stochastic modeling of the crime phenomenon in …

Research has increasingly moved toward a consensus that violent crime declines as
neighborhoods gentrify, yet some studies find the direction of this relationship varies by type …

A network‐enabled event log mining approach is proposed for a deep understanding of the
Building Information Modeling (BIM)‐based collaborative design work. It proposes a novel …

Spectral clustering is widely used in data mining, machine learning and other fields. It can
identify the arbitrary shape of a sample space and converge to the global optimal solution …

Soft overlapping clustering is one of the notable problems of community detection. Extensive
research has been conducted to develop efficient methods for nonoverlapping and crisp …

Many real-world systems can be abstracted as networks. As those systems always change
dynamically in nature, the corresponding networks also evolve over time in general, and …

As location-based services using mobile devices have become globally popular these days,
social network analysis (especially, community detection) increasingly benefits from …

The overall goal of this project is to advance a new analytical platform tailor-designed to
probe single extracellular vesicles (EVs). Specifically, we will develop a new imaging …

Community is a common characteristic of networks including social networks, biological
networks, computer and information networks, to name a few. Community detection is a …