Probabilistic graph query processing techniques address the challenge of querying networks in which the presence of nodes or edges is uncertain. Such graphs arise in domains as varied as ...

In this tutorial step, you query your graph by using GQL (Graph Query Language) in the code editor. GQL provides powerful querying capabilities for complex graph ...

Abstract: Graph matching, as an important query technology, has been widely applied in various fields. With the increasing of graph data, users choose to encrypt a large number of graphs and store ...

In this tutorial, we implement a production-grade, large-scale graph analytics pipeline in NetworKit, focusing on speed, memory efficiency, and version-safe APIs in NetworKit 11.2.1. We generate a ...

Abstract: With the advent of graph data, graph databases have garnered significant research interest and efforts in recent years, especially with respect to graph query processing. There have been a ...

Semantic parsing converts natural language into formal query languages such as SQL or Cypher, allowing users to interact with databases more intuitively. Yet, natural language is inherently ambiguous, ...

ABSTRACT: In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The ...

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Add a description, image, and links to the graph-db topic page so that developers can more easily learn about it.

Ontotext, a semantic knowledge graph provider, announced that its flagship product, GraphDB, is now available on the Microsoft Azure Marketplace, enabling enterprises to streamline the global ...