GraphNews

We wanted to see if the sensor data can be brought together through the Node Red low-code/no-code framework to feed the data into RDFox, an in-memory triplestore and then data summaries periodically pushed to a central, larger triplestore.

Due to the fact that the chapters are related to each other, I realized my book is better represented with a graph than in a linear formatYou can see the "Values" chapter is the core, so many other parts come from that pic.twitter.com/lFsxG0U7M6— Sarah Drasner (@sarah_edo) July 13, 2021

Graph neural networks are intimately related to partial differential equations governing information diffusion on graphs.

Wouldn't it be great if AI could reason with commonsense knowledge?Check out our latest blog post on a new question answering model, QA-GNN, that jointly reasons with language models and knowledge graphs, by @michiyasunaga!https://t.co/6b6e7ZWCba— Stanford AI Lab (@StanfordAILab) July 13, 2021

Querying Linked Data: how to ensure user's quality requirements https://t.co/VtOKQ6HqJC pic.twitter.com/VOfDLNda5p— Aaron Bradley (@aaranged) July 14, 2021

An ontology for the formalization and visualization of scientific knowledge https://t.co/ZWx7UUwyzk pic.twitter.com/ATQlJfXoHw— Aaron Bradley (@aaranged) July 12, 2021

In this work we propose a new approach for semantic web matching to improve the performance of Web Service replacement. Because in automatic systems we should ensure the self-healing,...

In the previous SPHERE news article focusing on the application of ontologies for digital twins of buildings, the importance of interoperability between data environments was stressed to reach a rich digital representation. In our philosophy, applications in the SPHERE ecosystem should always be replaceable to avoid vendor-lock in and to stimulate a best-of-breed approach. Such ... Read more

#DataMatters course "Using Linked Data," taught by @balhoff, offers an introduction to #linkeddata, #knowledgegraphs, and the semantic web tools underlying its use. #datascience #dataanalytics @RENCI Learn more and register here: https://t.co/P23ZlCsVOQ https://t.co/AFx1FmN6vl

Here is my new article about best practices in designing object type libraries #RDF #ontology #linkeddata #OTL #BIM... 11 comments on LinkedIn

Geometric Deep Learning on Molecular Representations Atz et al.: https://lnkd.in/dEeydSb #ChemicalPhysics #ArtificialIntelligence #Biomolecules...

https://lnkd.in/eWj8SW2 How do graph databases work under the hood and how is this different from relational databases? In this, Will It Graph blog series...

David Meza, senior data scientist at NASA, and his team are building a talent mapping database to better identify talent for jobs.

As a data scientist or machine learning engineer it's not easy to keep up with the latest research. Zeta Alpha the next generation neural discovery platform...

Businesses need streaming ingestion tools and centralized data lakes with separate storage and compute layers to fulfill customer requests.

Graph Kernel Attention Transformers: Toward Expressive and Scalable Graph Processing | Synced...

Common sense knowledge graph embedding projected fasttext document embeddings vs transformers In these two blog posts, Radix demonstates deep learning...

Graphs algorithms, which are ideal to analyze sparse and irregular datasets, can benefit from special hardware that optimizes their performance.

While graph databases like Neo4j are schemaless by default, leverage the power of schemas in development by focusing on application driven graph schema design

Until very recently, the objects of common use such as wearable devices, cars, watches, refrigerators and health-monitoring devices, did not produce or handle d

Learning Attributed Graph Representations with Communicative Message Passing Transformer • Constructing appropriate representations of molecules lies at...

Leveraging the network structure of the use case to boost predictive performance

The application of graph analytics to various domains have yielded tremendous societal and economical benefits in recent years. However, the increasingly widespread adoption of graph analytics...

How do knowledge graphs influence artificial intelligence? Here's how looking at the relat

A hands-on overview with a real world dataset