Graph learning for combinatorial optimization: a survey of state-of-the-art
Graphs have been widely used to represent complex data in many applications, such as e-
commerce, social networks, and bioinformatics. Efficient and effective analysis of graph data …
commerce, social networks, and bioinformatics. Efficient and effective analysis of graph data …
Efficient algorithms for densest subgraph discovery on large directed graphs
Given a directed graph G, the directed densest subgraph (DDS) problem refers to the finding
of a subgraph from G, whose density is the highest among all the subgraphs of G. The DDS …
of a subgraph from G, whose density is the highest among all the subgraphs of G. The DDS …
Truss-based community search over large directed graphs
Community search enables personalized community discovery and has wide applications in
large real-world graphs. While community search has been extensively studied for …
large real-world graphs. While community search has been extensively studied for …
VAC: vertex-centric attributed community search
Attributed community search aims to find the community with strong structure and attribute
cohesiveness from attributed graphs. However, existing works suffer from two major …
cohesiveness from attributed graphs. However, existing works suffer from two major …
Local community detection in multiple networks
Local community detection aims to find a set of densely-connected nodes containing given
query nodes. Most existing local community detection methods are designed for a single …
query nodes. Most existing local community detection methods are designed for a single …
Cohesive subgraph search over big heterogeneous information networks: Applications, challenges, and solutions
With the advent of a wide spectrum of recent applications, querying heterogeneous
information networks (HINs) has received a great deal of attention from both academic and …
information networks (HINs) has received a great deal of attention from both academic and …
Efficient size-bounded community search over large networks
The problem of community search, which aims to find a cohesive subgraph containing user-
given query vertices, has been extensively studied recently. Most of the existing studies …
given query vertices, has been extensively studied recently. Most of the existing studies …
Attribute-sensitive community search over attributed heterogeneous information networks
J Wang, L Zhou, X Wang, L Wang, S Li - Expert Systems with Applications, 2024 - Elsevier
Community search (CS) over attributed heterogeneous information networks (AHINs) takes
both network structure and attributes of nodes into consideration, which can support …
both network structure and attributes of nodes into consideration, which can support …
Query driven-graph neural networks for community search: from non-attributed, attributed, to interactive attributed
Given one or more query vertices, Community Search (CS) aims to find densely intra-
connected and loosely inter-connected structures containing query vertices. Attributed …
connected and loosely inter-connected structures containing query vertices. Attributed …
On directed densest subgraph discovery
Given a directed graph G, the directed densest subgraph (DDS) problem refers to the finding
of a subgraph from G, whose density is the highest among all the subgraphs of G. The DDS …
of a subgraph from G, whose density is the highest among all the subgraphs of G. The DDS …