Utilizing knowledge graphs is one popular solution to drive up the performance of AI applications. We work closely together with other key players such as Emil…
RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF knowledge graphs, based on SHACL constraints
In the past year or so, our research team designed, developed and published RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF…
RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF knowledge graphs, based on SHACL constraints
Do LLMs Really Adapt to Domains? An Ontology Learning Perspective
Large Language Models (LLMs) have demonstrated unprecedented prowess across various natural language processing tasks in various application domains. Recent studies show that LLMs can be leveraged...
An easy trick to improve your LLM results without fine-tuning. Many people know "Few-Shot prompting" or "Chain of Thought prompting". A new (better) method was… | 77 comments on LinkedIn
Episode #212: Digging Into Graph Theory in Python With David Amos – The Real Python Podcast
Have you wondered about graph theory and how to start exploring it in Python? What resources and Python libraries can you use to experiment and learn more? This week on the show, former co-host David Amos returns to talk about what he's been up to and share his knowledge about graph theory in Python.
Foundations and Frontiers of Graph Learning Theory
Recent advancements in graph learning have revolutionized the way to understand and analyze data with complex structures. Notably, Graph Neural Networks (GNNs), i.e. neural network architectures...
Foundations and Frontiers of Graph Learning Theory
Gartner Report on Building Knowledge Graphs for AI
Knowledge graphs deliver semantically enabled data management to power a diverse range of AI applications. To successfully build knowledge graphs at an enterprise level, data and analytics leaders must take an agile approach to knowledge graph development.
When we progress from data to knowledge, there is what physicists call a phase change like the change from water to ice or from mud to brick. The ingredients are the same throughout the transition, but we compress and restructure these ingredients into something entirely new with dramatically differ
🥳 The Wait is Over! As promised from my last post (https://lnkd.in/g9_-9i8D), I took MSFT open-source GraphRAG for a 🏎️💨 road test via my JAM4RAG (Just… | 12 comments on LinkedIn
loading Microsoft Research GraphRAG data into Neo4j
Many people have asked about loading Microsoft Research #GraphRAG data into Neo4j. I wrote a quick notebook last night to import Documents, Chunks (TextUnit)… | 27 comments on LinkedIn
loading Microsoft Research hashtag#GraphRAG data into Neo4j
From building simple LLM agents to graph-based AI solutions
We switched from building simple LLM agents to graph-based AI solutions this year. In our experience, agentic graphs are the only way to 1) ensure high… | 44 comments on LinkedIn
rom building simple LLM agents to graph-based AI solutions this year.
An enterprise-grade implementation of Knowledge Graphs for LLM apps (Graph RAG)
There is a lot of noise about #KnowledgeGraphs for LLM apps. But we haven't seen an enterprise-grade implementation. This approach could be one. "The… | 11 comments on LinkedIn
There is a lot of noise about hashtag#KnowledgeGraphs for LLM apps. But we haven't seen an enterprise-grade implementation. This approach could be one.
How exactly do knowledge graphs work? Before you dive deep into GraphRAG, learn the basics of property graphs - each node and relation can store a structured…