Effective and efficient community search over large heterogeneous information networks
Recently, the topic of community search (CS) has gained plenty of attention. Given a query
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …
Machine learning for subgraph extraction: Methods, applications and challenges
Subgraphs are obtained by extracting a subset of vertices and a subset of edges from the
associated original graphs, and many graph properties are known to be inherited by …
associated original graphs, and many graph properties are known to be inherited by …
A survey of continuous subgraph matching for dynamic graphs
With the rapid development of information technologies, multi-source heterogeneous data
has become an open problem, and the data is usually modeled as graphs since the graph …
has become an open problem, and the data is usually modeled as graphs since the graph …
Reasoning like human: Hierarchical reinforcement learning for knowledge graph reasoning
Knowledge Graphs typically suffer from incompleteness. A popular approach to knowledge
graph completion is to infer missing knowledge by multi-hop reasoning over the information …
graph completion is to infer missing knowledge by multi-hop reasoning over the information …
Efficient and effective community search on large-scale bipartite graphs
Bipartite graphs are widely used to model relation-ships between two types of entities.
Community search retrieves densely connected subgraphs containing a query vertex, which …
Community search retrieves densely connected subgraphs containing a query vertex, which …
SEAL: Learning heuristics for community detection with generative adversarial networks
Y Zhang, Y **ong, Y Ye, T Liu, W Wang, Y Zhu… - Proceedings of the 26th …, 2020 - dl.acm.org
Community detection is an important task with many applications. However, there is no
universal definition of communities, and a variety of algorithms have been proposed based …
universal definition of communities, and a variety of algorithms have been proposed based …
Efficient algorithms for densest subgraph discovery
Densest subgraph discovery (DSD) is a fundamental problem in graph mining. It has been
studied for decades, and is widely used in various areas, including network science …
studied for decades, and is widely used in various areas, including network science …
[PDF][PDF] Vertex Priority Based Butterfly Counting for Large-scale Bipartite Networks.
Bipartite networks are of great importance in many realworld applications. In bipartite
networks, butterfly (ie, a complete 2× 2 biclique) is the smallest non-trivial cohesive structure …
networks, butterfly (ie, a complete 2× 2 biclique) is the smallest non-trivial cohesive structure …
Detecting communities from heterogeneous graphs: A context path-based graph neural network model
Community detection, aiming to group the graph nodes into clusters with dense inner-
connection, is a fundamental graph mining task. Recently, it has been studied on the …
connection, is a fundamental graph mining task. Recently, it has been studied on the …
A survey about community detection over On-line Social and Heterogeneous Information Networks
Abstract In modern Online Social Networks (OSNs), the need to detect users' communities
based on their interests and social connections has became a more and more important …
based on their interests and social connections has became a more and more important …