Now, it's extending this foundation using a vector database to enhance its existing knowledge graph and graph database for AI use cases. An essential component for building more trustworthy AI lies in ...

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management.

They require a knowledge graph. How does the journey to a knowledge graph start with unstructured data—such as text, images, and other media? The evolution of web search engines offers an ...

While document metadata are represented with Dublin Core and CIDOC-CRM, triples automatically extracted from the text are modeled with RDF reification ... the obtained graph is not de facto a ...

a U.K.-based knowledge graph startup that has built an AI reasoning engine that can be deployed on edge devices, for an undisclosed amount. Spun out of the University of Oxford, the startup was ...

Samsung said on Thursday that it has agreed to acquire Oxford Semantic Technologies, a UK-based startup with knowledge graph technology. The South Korean tech giant said combining such technology ...

To start building your knowledge graph, set up a Neo4j database. It will be the backbone of your project. You’ll use the Cypher query language to add, change, and find complex network data.

A knowledge graph is a graph-based database that represents knowledge in a structured and semantically rich format. This could be generated by extracting entities and relationships from structured ...

reification, and hyper-relations. To build the dataset, we create a new Knowledge Graph from the Crunchbase database using a lightweight schema to support high-quality entity embeddings in large ...