"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.

I keep seeing mentions of "entity-resolved knowledge graphs", which leads me to believe that other so-called "knowledge" graphs don't resolve their entities. But a knowledge graph without entity resolution is like a beach under deep snow and dark skies.

Hype Cycle for Data Management, 2024

How can we represent change in complex systems using Ontologies? In complex systems, understanding and representing change over time can be challenging. Basic… | 52 comments on LinkedIn

A step-by-step guide using Python

This is "Knowledge Graphs for Dummies! - Veronika Heimsbakk" by JavaZone on Vimeo, the home for high quality videos and the people who love them.

This article was based on Transmute Solutions Architect Nis Jespersen’s ‘UN/CEFACT Linked Data’ presentation from December 2022.

Knowledge Graph technologies are promising to implement in Business Intelligence Systems due to encoding different relations between…

How Knowledge Graphs aid in Complete Retrieval for Multi-Document RAG

Knowledge Graphs as Powerful Evaluation Tools for LLM Document Intelligence 📃 Organizations across industries are grappling with an unprecedented deluge of… | 57 comments on LinkedIn

A story about Ontotext's enterprise-grade knowledge graph for marketing content, SEO and knowledge management. In 2022 I had the chance to walk the thorny, as I would later find out, road of my PhD thesis talk towards a vision of marketing where we don’t manipulate the marketing mix, but rather mana

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Amazon Neptune Analytics now supports openCypher queries over RDF graphs. When you build an application that uses a graph database such as Amazon Neptune, you’re typically faced with a technology choice at the start: There are two different types of graphs, Resource Description Framework (RDF) graphs and labeled property graphs (LPGs), and your choice of […]

Discover more about what's new at AWS with Amazon Neptune Analytics now supports openCypher queries over RDF Graphs

Copyright 2024 Kurt Cagle / The Cagle Report From one of my readers: Hi Kurt, have you written any article on how a knowledge graph differ from inventory built using graph. We are in constant struggle to differentiate knowledge graph from inventory apps? Questions like can inventory systems built us

Google is the undisputed leader in web search – technically a monopoly in fact. The coverage of web properties (good and bad) is vast – about 400 billion documents – so in quantitative terms it's really very good.

What process and features are available for you to understand and iterate on the Schema, Graph Information, and Question interpretation.

Understanding the challenges of Generative AI in the age of open web. How GenAI technology can shape public discourse and information quality.

Introduction In my first article on LinkedIn, I discussed how to build an ontology from a corpus of text. My follow-up research for agnos.

Recent advancements in Large Language Models (LLMs) have showcased their proficiency in answering natural language queries. However, their effectiveness is hindered by limited domain-specific...

We're excited to announce the first release of SEOntology, an open-source framework developed to unify and standardize SEO data across the industry. SEOntology aims to address one of the pressing challenges in modern SEO: data fragmentation.

[vc_row][vc_column width=”1/2″ css=”.vc_custom_1724344160150{padding-right: 70px !important;}”][vc_column_text]In the era of AI, data quality has become a critical factor for successful implementations. A study by MIT Sloan Management Review found that 85% of executives believe AI will offer significant competitive advantages, yet only 39% have an AI strategy in place. This gap highlights the importance of foundational elements […]

Passing this along (because I think it shows how this field is evolving) but also to make a point. RAG is only half the story. Use RDF2Vec or a similar encoder…

Taxonomies and ontologies together are increasingly described as semantic models or semantic structures.