Samsung Electronics acquires Oxford Semantic Technologies, powering next generation knowledge graph and accurate AI technology.
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Features
Semantic Reasoning
Knowledge Graph Database
Performance
Deployment
On-Device
On-Cloud
Use Cases
Semantic Search & Recommendation
Rules & Regulation
Configuration Management
Autonomous Vehicles
Resources
Resource Hub
Blog
News
FAQs
White Papers
Patents
Developers
Documentation
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What does RDFox offer?
Unrivaled rules-based AI
The best load and query performance available anywhere
Memory-optimised for large data sets and on-device deployment
Enterprise features such as High Availability and Access Control
Unmatched stability
Decades of experience and research out of the University of Oxford
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Press Release
Samsung Electronics Announces Acquisition of Oxford Semantic Technologies, UK-Based Knowledge Graph Startup
Technical Article
Reasonable Vehicles Rule the Road
Business Article
ChatGPT’s ‘Snow White’ Problem: The Danger of Common Knowledge
Business Article
Unlocking AI’s Full Potential with Human-like Reasoning
FAQs
What is Knowledge Based AI?
What is materialisation?
What kind of rules can I write in RDFox?
What is backwards chaining?
What is a graph explorer?
What is an Ontology?
What is RDF?
What is semantic inference?
What is w3c? What are the w3c standards? Why do they matter?
What is an IRI? (What does IRI mean?)
What is a Knowledge Graph?
What is Incremental Reasoning?
How to query a graph database
Data relationships in a graph
What is OWL?
What is Faceted Search?
What is a ttl file?
What is Datalog?
What is a labeled property graph?
What is SHACL?
What is a Property Path?
What is a blank node?
What is the Google Knowledge Graph?
What is a graph database?
What is SPARQL?
How to build a knowledge graph?
What is negation as failure?
What is a named graph?
Why use a graph database?
What is a rule?
What is a constraint?
Relational vs non-relational databases
What is Semantic Reasoning?
What is a graph model?
What is a triple?
What is KRR (Knowledge Representation and Reasoning)?
What is RAG (Retrieval Augmented Generation)?
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