A research team from Kumamoto University has developed a promising deep learning model that significantly enhances the accuracy of subgraph matching — a critical task in fields ranging from ...

--MicroAlgo Inc.,, today announced the introduction of an innovative solution: a multi-simulator collaborative algorithm based on subgraph isomorphism, aimed at overcoming the limitations of qubit ...

Bug report I have deployed my subgraph on local graph node running v0.33.0 . Whenever reorg happens in ethereum my subgraph stops indexing for a long time and recovers itself later on . found 2 ...

As a fundamental problem in graph data mining, Densest Subgraph Discovery (DSD) aims to find the subgraph with the highest density from a graph. It has been studied for several decades and found a ...

Specifically, subgraph search query is one of the most popular query paradigms for accessing graph data. Since graphs are intuitive to draw, graph data management tools from academia and industry (for ...

Search over graph databases has attracted much attention recently due to its usefulness in many fields, such as the analysis of chemical compounds, intrusion detection in network traffic data, and ...

Chainstack Subgraphs intends to provide a convenient way for subgraph developers to migrate their APIs off the old The Graph hosted service, the announcement said.

GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

Subgraph matching problem is identifying a target subgraph in a graph. Graph neural network (GNN) is an artificial neural network model which is capable of processing general types of graph structured ...