GraphNews

The Pragmatic Evolution of Graph Data Models in Agentic Systems 🔬 The selection and implementation of appropriate graph paradigms for agentic systems…

SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph…

We're excited to announce the launch of the KGC Resource Hub (https://lnkd.in/gSaVmS8V), in collaboration with our friends at metaphacts GmbH! 🚀 The KGC…

How we used Kùzu in combination with LLMs in multiple stages of the Graph RAG pipeline to build a QA chatbot for the Connected Data London Knowledge Graph Challenge

codes explained with example, Generative AI

In today’s digital scenario, where AI-driven search and discovery platforms are redefining the rules of online engagement, businesses must rethink how they structure and present their data. At Connected Data London 2024, I had the privilege to speak about the transformative power of knowledge graphs

2024 is coming to an end and the holidays provide a little time to rest. If you are searching for an interesting read I can recommend our latest Data Powered…

As you enjoy your holiday season, I suggest two resolutions to consider for the New Year: entity resolution and relation resolution. Both will need to be priority #1 for a prosperous new year.

Why someone in a regulated industry should invest in #GraphRAG is something we have already discussed here: https://lnkd.in/d5ykdD7u With the associated…

How Semantic Partners converted the SFIA competency framework dataset to RDF, and made it available through the SFIA foundation.

This article demonstrates how developers or investigative journalists can use Senzing entity resolution (ER) to work with unstructured documents. In particular, given that ER has been used with structured data sources to construct a domain-specific KG, the results of ER can be leveraged to customise entity linking (EL) downstream, for example using spaCy — as an alternative to off-the-shelf EL sources such as DBPedia.

Empower enterprises to turn strategy into action! As a Knowledge Engineer at In Parallel, you'll craft ontologies and knowledge graphs to drive AI-powered strategic alignment and execution. Joi...

ICYMI, here are the slides from our standing room only talk at NeurIPS yesterday! Concepts we discuss include: ➡️ Quantifying how much Transformer you need to… | 18 comments on LinkedIn

Help us shape the future of RDF shape languages: share your insights Are you working with #RDF shape languages like #SHACL or #ShEx? Whether you’re a…

My colleague Su Zun and I spent a very enjoyable 3 days last week with the linked data community at Connected Data London. It was fantastic, and I'm so looking…

Showcase of Data Transformation Process, Breakdown of 20 dev hours involved, Schemas used, Questions & Responses, and Graph created

Following up on participation in the Connected Data London conference last week, my latest blog post is "Ontologies vs. Knowledge… | 13 comments on LinkedIn

GraphRAG is a powerful retrieval mechanism that improves Generative AI applications by taking advantage of the rich context in graph data structures.

🚀 R2R : The Most Advanced AI Retrieval System We're excited to announce R2R's V3 API, bringing production-ready RAG capabilities to teams building serious AI… | 10 comments on LinkedIn

An ontology is like a map of your organisation’s knowledge, built on the concepts and relationships that define your domain. Think of it as your company’s… | 20 comments on LinkedIn

A Conceptual Overview for Building Robust Solutions.

In this issue: A new standard for GraphRAG Replicating OpenAI’s strongest model LLM-”brained” agents for your devices Upgrade here 1. LazyGraphRAG: Setting a new standard for quality and cost Watching: LazyGraphRAG (blog) What problem does it solve? Retrieval Augmented Generation (RAG) has become a

SQL vs SPARQL: Two Titans of Data Querying 💻 When it comes to extracting valuable insights from data, SQL and SPARQL are often compared. But did you know…

Graphs + Transformers = the best of both worlds 🤝 The same models powering breakthroughs in natural language processing are now being adapted for graphs…

Our algorithm GNN: Graph Neural Network and Large Language Model Based for Data Discovery inherits the benefits of [Hoang(2024b)] (PLOD: Predictive Learning Opt

A Graph Neural Network (GNN) won the highly competitive Causal Discovery competition arranged by ADIA Lab. Of course I mean to say that Hicham Hallak won the… | 19 comments on LinkedIn

Agentic Graph Intelligence 🕳️ Agentic graph reasoning represents a sophisticated cognitive architecture that integrates multiple advanced components into a…

Enterprise GraphRAG: Building Production-Grade LLM Applications with Knowledge Graphs Let’s dive into the numbers: Real-World Results Implementing GraphRAG…