Given a directed graph G, the directed densest subgraph (DDS) problem refers to finding a
subgraph from G, whose density is the highest among all subgraphs of G. The DDS problem …

The densest subgraph problem has received significant attention, both in theory and in
practice, due to its applications in problems such as community detection, social network …

Identifying dense subgraphs called quasi-cliques is pivotal in various graph mining tasks
across domains like biology, social networks, and e-commerce. However, recent algorithms …

Locally-densest subgraph (LDS) decomposition is a fundamental decomposition in graph
analysis that finds numerous applications in various domains, including community …

We introduce the triangle-densest-k-subgraph problem (TDkS) for undirected graphs: given
a size parameter k, compute a subset of k vertices that maximizes the number of induced …

Signed networks, characterized by edges labeled as either positive or negative, offer
nuanced insights into interaction dynamics beyond the capabilities of unsigned graphs …

Densest subgraph discovery (DSD) is a fundamental topic in graph mining. It has been
extensively studied in the literature and has found many real applications in a wide range of …

Sharding is a promising technique for increasing a blockchain system's throughput by
enabling parallel transaction processing. The main challenge of state sharding lies in …

With the prevalence of data-driven intelligence, data markets with various data products are
gaining considerable interest as a promising paradigm for commoditizing data and …

As a fundamental topic in graph mining, Densest Subgraph Discovery (DSD) has found a
wide spectrum of real applications. Several DSD algorithms, including exact and …