Neural subgraph counting with Wasserstein estimator
Subgraph counting is a fundamental graph analysis task which has been widely used in
many applications. As the problem of subgraph counting is NP-complete and hence …
many applications. As the problem of subgraph counting is NP-complete and hence …
Efficient Exact Subgraph Matching via GNN-Based Path Dominance Embedding
The classic problem of exact subgraph matching returns those subgraphs in a large-scale
data graph that are isomorphic to a given query graph, which has gained increasing …
data graph that are isomorphic to a given query graph, which has gained increasing …
Neural Attributed Community Search at Billion Scale
Community search has been extensively studied in the past decades. In recent years, there
is a growing interest in attributed community search that aims to identify a community based …
is a growing interest in attributed community search that aims to identify a community based …
Efficient Exact Subgraph Matching via GNN-based Path Dominance Embedding (Technical Report)
The classic problem of exact subgraph matching returns those subgraphs in a large-scale
data graph that are isomorphic to a given query graph, which has gained increasing …
data graph that are isomorphic to a given query graph, which has gained increasing …
Intrinsically motivated graph exploration using network theories of human curiosity
Intrinsically motivated exploration has proven useful for reinforcement learning, even without
additional extrinsic rewards. When the environment is naturally represented as a graph, how …
additional extrinsic rewards. When the environment is naturally represented as a graph, how …
Community search: a meta-learning approach
Community Search (CS) is one of the fundamental graph analysis tasks, which is a building
block of various real applications. Given any query nodes, CS aims to find cohesive …
block of various real applications. Given any query nodes, CS aims to find cohesive …
BF-BigGraph: An efficient subgraph isomorphism approach using machine learning for big graph databases
A Yazici, E Taşkomaz - Information Systems, 2024 - Elsevier
Graph databases are flexible NoSQL databases used to efficiently store and query complex
and big data. One of the most difficult problems in graph databases is the problem of …
and big data. One of the most difficult problems in graph databases is the problem of …
PathLAD+: Towards Effective Exact Methods for Subgraph Isomorphism Problem
Y Wang, C Jin, S Cai - Artificial Intelligence, 2024 - Elsevier
The subgraph isomorphism problem (SIP) is a challenging problem with wide practical
applications. In the last decade, despite being a theoretical hard problem, researchers …
applications. In the last decade, despite being a theoretical hard problem, researchers …
[PDF][PDF] PathLAD+: An Improved Exact Algorithm for Subgraph Isomorphism Problem.
The subgraph isomorphism problem (SIP) is a challenging problem with wide practical
applications. In the last decade, despite being a theoretical hard problem, researchers …
applications. In the last decade, despite being a theoretical hard problem, researchers …
[PDF][PDF] Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries.
G Sharmila, MK Devi - Computer Systems Science & …, 2023 - cdn.techscience.cn
Over the past era, subgraph mining from a large collection of graph database is a crucial
problem. In addition, scalability is another big problem due to insufficient storage. There are …
problem. In addition, scalability is another big problem due to insufficient storage. There are …