GraphNews

500 million+ members | Manage your professional identity. Build and engage with your professional network. Access knowledge, insights and opportunities.

500 million+ members | Manage your professional identity. Build and engage with your professional network. Access knowledge, insights and opportunities.

This article discusses why benchmarking is important, as well as compare and contrasts Neo4j’s 100TB demo with TigerGraph.

Framework for zero-shot learning with knowledge graphs. - GitHub - BatsResearch/zsl-kg: Framework for zero-shot learning with knowledge graphs.

WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset Wang et al.: https://lnkd.in/dk8nCAjT #ArtificialIntelligence #DeepLearning #MachineLearning...

Criteo AI Lab is excited to be presenting Graph Machine Learning in Industry. Please join us on Thursday, September 23rd, at 17:00 Paris time. This page will be updated with video links after the workshop.

Keeping track of faculty research activities, using semantic data integration of public LOD sources combined into a single knowledge graph

The Data Exchange Podcast: Paco Nathan on recent trends in large-scale graph technologies and novel applications of graph databases.

What components are needed for building learning algorithms that leverage the structure and properties of graphs?

Stanford is proud to organize a workshop that  brings together leaders from academia and industry to showcase recent advances in Graph Neural Networks.... 45 comments on LinkedIn

Dr. Alicia Frame, director of graph data science at Neo4j, explains how graph technology could ameliorate the end of the third-party cookie

Yesterday I presented the paper "Graph? Yes! Which one? Help!" at the SEMANTiCS 2021 conference (co-authored with several colleagues from the Neptune team...

500 million+ members | Manage your professional identity. Build and engage with your professional network. Access knowledge, insights and opportunities.

I'm relatively old school, semantically speaking: my first encounters with RDF was in the early 2000s, not long after Tim Berners-Lee's now-famous article in Scientific American introducing the Semantic Web to the world.

Graph database query languages are growing, along with graph databases. They let developers ask complex questions and find relationships.

Types x Individuals, Instantiation x Specialization. These are among the most fundamental distinctions in Conceptual Modeling. Still, they seem to elude... 23 comments on LinkedIn

Leveraging more data sources using machine learning on graphs to enhance item suggestions for Decathlon members

Content management and its many challenges Content is inherently diverse, written for and understandable only by a specific audience, often multilingual, scattered across silos and different systems, and regularly ambiguous and therefore difficult to understand. Even humans, who are actually experts

Gartner has put “Knowledge Graphs” at the peak of inflated expectations. If you are a Knowledge Graph software vendor, this might be good news. Companies will be buying knowledge graphs without knowing what they are. I’m reminded of an old cartoon of an executive dictating into a dictation machine: “…and in closing, in the future […]

And the Quest for a New Business Model for Open Source Projects

Researchers are turning to the mathematics of higher-order interactions to better model the complex connections within their data.

Very honored to have been invited by Jesús Barrasa Amy Hodler and Jim Webber to write the foreword for their book "Knowledge Graphs Data in Context for...

As data grows at an exponential rate, TigerGraph aims to make its graph database an attractive choice for data management because of its ability to scale.

🤖 A Python library for learning and evaluating knowledge graph embeddings - GitHub - pykeen/pykeen: 🤖 A Python library for learning and evaluating knowledge graph embeddings

Reply to "Why I Don't Use OWL Anymore" by Irene Polikoff - In recent years, many linked data experts have reflected on the use of SHACL in…

This course is aimed at digitization managers and data scientists who are responsible for datasets and knowledge management and helps you to improve the handling of information. Using various knowledge graph tools as examples, learn how to network your datasets and build a digital knowledge base in this course.

Last year, we have announced our collaboration with Google Maps on deploying a graph neural network for estimating expected travel times (ETAs), which ... 31 comments on LinkedIn