GraphNews

Just learned yesterday that GNOME has been using SPARQL in desktop search for quite a while—and I had no idea! 😲 Turns out their tool, "Tracker", is powered…

🚀 PyG 2.6 is here! 🎉 We’re excited to announce the release of PyG 2.6.0, packed with incredible updates for graph learning! Here’s a quick rundown of what’s… | 14 comments on LinkedIn

Your first ontology doesn’t need to be an ontology. Here’s what I mean. Combining ontologies with knowledge graphs is a powerful approach. But implementing… | 21 comments on LinkedIn

Elevating RAG accuracy and performance by structuring long documents into explorable graphs and implementing graph-based agent systems

Graph neural networks (GNNs) are a type of neural network capable of learning on graph-structured data. However, training GNNs on large-scale graphs is challenging due to iterative aggregations of...

Hey Knowledge Graph friends! As I imagine some of you are, I've been a bit annoyed that many "Knowledge Graph and AI" demos and tools—while definitely… | 13 comments on LinkedIn

How do you maintain an ontology over time? Today, I had a wonderful meeting with Kurt Cagle about ontologies, AI, and beyond. We spent some time on this… | 27 comments on LinkedIn

Design patterns for improving GenAI applications with a graph.

Finding the perfect GraphRAG pattern demands experimentation with different retrieval patterns

Pushing AI On-Device with GraphRAG 🚀. Contribute to trustgraph-ai/trustgraph development by creating an account on GitHub.

#Alhamdulillah, Our iText2KG has achieved over 300 stars and 27 forks in just 10 days after its release, and it is currently ranked among the top 12 trending…

Your first ontology doesn’t need to be an ontology. Here’s what I mean. Combining ontologies with knowledge graphs is a powerful approach. But implementing…

Web Ontology Language (OWL) emerges as a superior choice for knowledge representation in generative AI, offering unparalleled expressiveness, reasoning capabilities, and semantic richness. By leveraging OWL-based knowledge graphs, AI systems can generate more accurate, context-aware, and nuanced outputs across diverse ...

As the volume of digital content increases, the ability to manage it becomes more important. Taxonomy and metadata are vital to finding products, conducting scientific research, and keeping track of organizational information. They also enable a wide variety of analytics on unstructured data. We can see the results of a well-designed taxonomy, but behind the scenes, there's a lot more going on than meets the eye.

My presentation at the "First International Workshop on Scaling Knowledge Graphs for Industry" at the SEMANTICS 2024 Conference in Amsterdam was focused on the…

DOM Graph RAG: A semantic content architecture for neuro-symbolic RAG

Introduction

i want to share the actual steps we’re using to generate text to sql through an ontology instead of an LLM [explained with a library analogy]: 𝟭… | 15 comments on LinkedIn

Covering the advanced RAG options in R2R

The growing ubiquity of relational data structured as graphs has underscored the need for graph learning models with exceptional generalization capabilities. However, current approaches often...

✨ Operationalizing the information architecture 👇 There are three main ways to operationalize the information architecture, depending on how the data plane… | 14 comments on LinkedIn

A Step-by-Step Tutorial on Implementing Retrieval-Augmented Generation (RAG), Semantic Search, and Recommendations

"From Semiotic to Digital Enterprise Semantic Interoperability? Translation in english with some completion of my last article in French. Enterprises are…

GraphRAG uses LLM-generated knowledge graphs to substantially improve complex Q&A over retrieval-augmented generation (RAG). Discover automatic tuning of GraphRAG for new datasets, making it more accurate and relevant.

Have you ever entered a news-spelunking time-machine 🧗? Well AskNews built one...and our users are already jumping into the time-machine to explore the…

An example of the application of #LegalKit is the production of knowledge #graphs, here is a Hugging Face demo #Space 🤗 With the update of the French legal…

Where do you start when you want to build an ontology? Building an ontology sounds like a big, complex task, right? With all those high-level frameworks like… | 28 comments on LinkedIn

Establishing this open data portal to share our reference data and schema with customers, stakeholders, and partners under a permissive open data license.