The Wikipedia Republic of Literary Characters | Published in Journal of Cultural Analytics
By Paula Wojcik, Bastian Bunzeck & 1 more. This articles explores character representations in Wikidata across various language editions.
GraphNews
Explore OntoGPT for Schema-based Knowledge Extraction
The OntoGPT framework and SPIRES tool provide a principled approach to extract knowledge from unstructured text for integration into Knowledge Graphs (KGs), using Large Language Models such as GPT. This methodology enables handling complex relationships, ensures logical consistency, and aligns with predefined ontologies for better KG integration.
The OntoGPT framework and SPIRES tool provide a principled approach to extract knowledge from unstructured text for integration into Knowledge Graphs (KGs), using Large Language Models such as GPT. This methodology enables handling complex relationships, ensures logical consistency, and aligns with predefined ontologies for better KG integration
Graph Database
Data Graphs drinks its own Champagne
A Content Graph case study on how the Data Graphs website is self powered - entirely knowledge graph driven
StandICT.eu_Landscape of Ontologies Standards_V1.0.pdf
The inclusion of 'Ontology and Graphs' in Gartner's hype cycle report signifies growing maturity and acceptance as a practical solution
Ontology adoption extends beyond managing taxonomy and glossary, encompassing areas such as natural language processing, big data and machine learning, cyber-physical systems, FAIR data, model-based engineering & digital twins
This comprehensive survey of the Landscape of Ontologies Standards presents a curated collection of ontologies that are highly relevant to ICT domains and vertical sectors, considering their maturity, prominence, and suitability for representing linked data in the #semanticweb
A Landscape of Ontologies Standards (Report of TWG Ontologies) | StandICT.eu 2026
The inclusion of 'Ontology and Graphs' in Gartner's hype cycle report signifies growing maturity and acceptance as a practical solution
Ontology adoption extends beyond managing taxonomy and glossary, encompassing areas such as natural language processing, big data and machine learning, cyber-physical systems, FAIR data, model-based engineering & digital twins
This comprehensive survey of the Landscape of Ontologies Standards presents a curated collection of ontologies that are highly relevant to ICT domains and vertical sectors, considering their maturity, prominence, and suitability for representing linked data in the #semanticweb
Pisa, Italy - 24 May 2023] - The StandICT.eu Technical Group for ICT under the European Observatory for ICT Standardisation (EUOS) has formed a special interest group comprising domain experts, ontologists, and researchers from academia and industry. Together, they have conducted a comprehensive survey of the Landscape of Ontologies Standards.
The result of their months-long effort is a remarkable report, now released by the StandICT.eu 2026 community. This report presents a curated collection of ontologies that are highly relevant to ICT domains and vertical sectors, considering their maturity, prominence, and suitability for representing linked data in the semantic web.
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Since their emergence in Gartner's Emerging Technologies report in 2001, Ontology engineering has steadily progressed, primarily through academic efforts to support the semantic web stack. The recent inclusion of 'Ontology and Graphs' in Gartner's "hype cycle" report in 2020 signifies its growing maturity and acceptance as a practical solution for numerous ICT applications. Today, Ontology adoption extends beyond managing taxonomy and glossary, encompassing areas such as natural language processing, big data and machine learning, cyber-physical systems, FAIR data, model-based engineering, digital twin, and thread.
Structure-inducing pre-training
Nature Machine Intelligence - Designing methods to induce explicit and deep structural constraints in latent space at the sample level is an open problem in natural language processing-derived...
A Hyperparametrization Is All You Need - Building a Recommendation System for Telecommunication Packages Using Graph Neural Networks
Graph Neural Networks can be used for a variety of applications but do you know what it takes to create a great recommendation system? Dive deep into the math of GNNs, implement a link prediction module and show everyone how stunning graph machine learning can be!
TODA, EMS & Graphs – New Enterprise Architectural Tools For A New Age
Change & Risk Require New Enterprise Tools As AI systems, bots (both digital and physical), AI leveraged smart digital identities, and IoT devices invade your enterprise, it increases the pace of change and risk. This brief article focuses on why you should be deploying TODA, EMS and graphs in your
TODA, EMS & Graphs – New Enterprise Architectural Tools For A New Age”
ArangoDB Boosts Performance and Usability Across Search, Graph, and Analytics with Release of ArangoDB 3.11
SAN FRANCISCO, May 30, 2023 -- ArangoDB, the company behind the most complete graph data and analytics platform, today announced the GA release of
Ontotext Receives Growth Funding to Ride the Growing Demand for Graph Technology
Ontotext receives growth funding to strengthen its leadership in the knowledge graph market and develop end-to-end vertical offerings.
$7+ Billion Graph Database Market Size to Grow at 22+% CAGR by 2028 - The Insight Partners
The Graph Database Market size is driven by the increasing use of graph database tools and services based on artificial intelligence (AI) and the rising...
Interoperable between data and policies is key. On the web, interoperability for pages is HTML. For data, it’s RDF. For people and policies it’s Solid
This week I was very fortunate to be invited to attend the honorary degree ceremony of Sir Tim Berners-Lee by the London School of Economics. The title of…
Interoperable between data and policies is key. On the web, interoperability for pages is HTML. For data, it’s RDF. For people and policies it’s Solid
Internet Meme Knowledge Graph
Don't make directed graphs undirected! Introducing Dir-GNN, extending any spatial MPNN to handle directed graphs
Don't make directed graphs undirected! Introducing Dir-GNN, extending any spatial MPNN to handle directed graphs. Preserving edge directionality is crucial…
Don't make directed graphs undirected! Introducing Dir-GNN, extending any spatial MPNN to handle directed graphs
Multiple Vendors Make Data and Analytics Ubiquitous
News from eight different companies shows analytics, data management, streaming data and AI are increasingly intermingled, all in the cloud.
weblog/README.md at master · justin2004/weblog · GitHub
a weblog. Contribute to justin2004/weblog development by creating an account on GitHub.
A Guide to ICLR 2023 — 10 Topics and 50 papers you shouldn't miss
The 2023 International Conference on Learning Representations is going live in Kigali on May 1st, and it comes packed with more than 2300 papers. Reasoning in Language Models, Diffusion, Self supervised learning for Computer Vision, Molecular Modeling, Graph Neural Networks, Federated Learning, and much more... Here's our guide to get you started. The role of conferences in the modern world of ML research has shifted. Previously seen as a platform for disseminating cutting-edge research, confere
Global Graph Analytics Market Analysis Report 202: A $6.9 Billion Market by 2028 from $1.14 Billion in 2022 - Increasing Adoption of Graph AI & Surge in Adoption of Machine Learning
Dublin, April 24, 2023 (GLOBE NEWSWIRE) -- The "Global Graph Analytics Market: Analysis By Component, By Deployment, By Enterprise Size, By Application,...
Recursion Enters into Agreements to Acquire Cyclica and Valence to Bolster Chemistry and Generative AI Capabilities | Recursion Pharmaceuticals, Inc.
SALT LAKE CITY and TORONTO and MONTRÉAL , May 08, 2023 (GLOBE NEWSWIRE) -- Recursion (NASDAQ: RXRX), a leading clinical stage TechBio company decoding biology to industrialize drug discovery, today announced it has signed agreements to acquire two companies in the AI-enabled drug discovery space:
Graph Query Language GQL
May 16, 2023 – GQL Status Update
In February, 2023, the GQL standards committee (ISO/IEC JTC1 SC32 WG3) had a week-long meeting in Zeist, Netherlands, where we reviewed and accepted papers that completed the resolution of all of the GQL CD2 comments. The editors applied the papers, the authors
Graph Database Market Size, Industry Share, Emerging Trends & Opportunities | MarketsandMarkets™
The global graph database market size is projected to grow at a compound annual growth rate (CAGR) of 22.5% to reach USD 5.1 billion in the upcoming five years. The market value was USD 1.9 billion in 2021.
“GraphGPT is a system that uses GPT, a language model developed by OpenAI”
We interviewed Varun Shenoy, a senior at Stanford who created a tool named GraphGPT.
GraphGPT: convert unstructured natural language into a knowledge graph
By Dr. Verónica Espinoza, 2023 / Twitter @Verukita1
the RDF-star Working Group at W3C has published 16 First Public Working Drafts, which represent the first milestone in the update of the #RDF and #SPARQL families of specification towards version 1.2
📢 the RDF-star Working Group at W3C has published 16 First Public Working Drafts, which represent the first milestone in the update of the #RDF and #SPARQL…
the RDF-star Working Group at W3C has published 16 First Public Working Drafts, which represent the first milestone in the update of the #RDF and #SPARQL families of specification towards version 1.2
Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
Nature Chemical Biology - Using a neural network trained on bacterial growth inhibition data, in silico prediction of molecules with activity against Acinetobacter baumannii led to the...
GraphML News May 6 2023.md
Graph ML News (May 20th)
Graph ML News (May 20th) The NeurIPS deadline has passed so we could finally disconnect from the cluster, breathe in some fresh air and get ready for the supplementary deadline and/or paper bidding depending on your status. The Workshop on Mining and Learning with Graph (MLG) at KDD’23 accepts submissions until May 30th. This year KDD will feature both MLG and Graph Learning Benchmarks (GLB), so two more reasons to visit Long Beach and chat with the fellow graph folks 😉 CS224W, one of the best graph courses from Stanford, started publishing project reports of the Winter 2023 cohort: some new articles include solving TSP with GNNs, approaching code similarity, and building music recommendation system with GNNs. More reports will be published within the next few weeks. Weekend reading: DRew: Dynamically Rewired Message Passing with Delay feat. Michael Bronstein and Francesco Di Giovanni (ICML’23) Random Edge Coding: One-Shot Bits-Back Coding of Large Labeled Graphs (ICML’23) Can Language Models Solve Graph Problems in Natural Language? On the Connection Between MPNN and Graph Transformer
Democratize Graph Data with Process Tempo
Unlock Neo4j's power with Process Tempo by connecting non-technical users to graph data insights at scale
Report: From Notetaking to Neuralink | A Contrary Research Deep Dive
A deep dive from Contrary Research. AI has the potential to transform how humans process information in their own knowledge management systems.