The enterprise knowledge graph is a knowledge representation system based on graph structures. It integrates multi-source data from both internal and external sources (such as business information, ...

The chatbot leverages Stardog’s pioneering knowledge graph platform, which is a flexible and reusable data layer that can ...

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

The core of this patent lies in its ability to generate multimodal hybrid interview questions. The system dynamically generates personalized interview questions based on candidates' resumes and ...

Weave Network Topology Agent from Articul8 ingests network logs, configuration files, and traffic data and transforms it into ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional ...

Jim Morris, solution engineer, Progress, and Stephen Reed, senior account manager, Progress, joined DBTA's webinar, Building Knowledge Graphs to Power Your AI Initiatives, to examine how knowledge ...

A study led by Jun Cheng from Xiamen University and collaborators introduces a new workflow for recommending relay catalysis pathways. The workflow uses large language models (LLMs) to extract and ...

AI is redefining how humans interact with technology by delivering deeply personalized, private, and secure experiences.

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

Neo4j also trumpeted the value of graphs as vector databases used in generative artificial intelligence. AI training requires ...