Oracle announces agentic AI capabilities for Oracle AI Database, including Private Agent Factory, Deep Data Security, and ...

New agentic AI capabilities designed for business data accelerate enterprise innovation and help defend enterprises from AI-era threats Available on all ...

PySemantic lets you define your data models as Python objects -- dimensions, measures, and entity relationships -- and generates correct, optimized SQL from simple metric queries. No more hand-writing ...

Databricks provides tables designed for massive scale, enabling efficient storage and querying of tens of billions of triples with features like time travel No ETL or migration needed—just query your ...

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: The temporal knowledge graph (TKG) query facilitates the retrieval of potential answers by parsing questions that incorporate temporal constraints, regarded as a vital downstream task in the ...

As AI-generated answers take over the search landscape, understanding what gets cited – and why – has never been more critical. Explore citation data across leading AI engines, see how B2B and B2C ...

We present unsupervised methods for training relation detection models from the semantic knowledge graphs of the semantic web. The detected relations are used to synthetically generate natural ...