GraphNews

Using knowledge graphs to improve the performance of RAG systems by optimising retrieval design architectures and collaborative filtering.

Knowledge Graph Embedding (KGE) algorithms can improve the performance of LLMs in understanding relationships as a context for Q&As.

Learn how to use unstructured.io for PDF document parsing, extracting, and ingestion into the Neo4j graph database for GenAI applications.

Let’s talk about the new graph-based approach to processing complex datasets for context-rich LLM responses

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.

RAG-Native Graph Creation have several misconceptions from traditional graph creation. We look to tackle some of these misconceptions.

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...

𝗥𝗔𝗚 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗙𝗮𝗶𝗹 𝗗𝘂𝗲 𝗧𝗼 𝗜𝗻𝘀𝘂𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗙𝗼𝗰𝘂𝘀 𝗢𝗻 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗜𝗻𝘁𝗲𝗻𝘁 𝘛𝘩𝘦 𝘔𝘪𝘯𝘥𝘧𝘶𝘭-𝘙𝘈𝘎… | 12 comments on LinkedIn

Additionally, there are evaluation methods where LLMs serve as the evaluators, including single point, reference-based, and pairwise-based…

Get rid of hallucination's and inconsistencies.

Graph-Powered Analytics And Machine Learning With TigerGraph - Driving Business Outcomes with Connected Data

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.

The Advantages of Small Graphs for Construction, Retrieval, Maintenance and Scaling KG RAG systems.

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

Ten Arguments

🥳 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

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

Examples of KG + RAG & Schemas that are used by various systems across different domains, for inspirational purposes.

An Overview of Knowledge Graph Embeddings (KGEs) – Part 1. 🧠🍄 Knowledge Graphs represent real-world facts as structured data. Nodes represent entities or…

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

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

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…

AI Reasoning on Cybersecurity RDF Graphs https://lnkd.in/dAKb43bV Allen Woods, Tony Seale, Andrey Prozorov, Andy Watkin-Child CSyP, CEng, MSyI, MIMechE… | 10 comments on LinkedIn

This is something very cool! 3. GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models "GraphReader addresses the…

Discover why GraphRAG will subsume vector-only RAG and emerge as the default RAG architecture for most use cases.

Interactive Network Graphs for Uncovering Complex Multicollinearity 🕸️ Visualize multicollinearity in large datasets with interactive network graphs using… | 18 comments on LinkedIn

See how to combine structured and unstructured semantic queries and to use large language models to orchestrate question answering over a knowledge graph.

This weekend we released a first version of JSON-LD Framing of DFRNT hypergraphs, that is now exposed as a user interface. This is great for technical…

Recently, Microsoft announced with a post their GraphRAG offering. This article provides a brief overview of their approach, how it compares to other Graph RAG varieties, what problems it can address and what it cannot.