GraphNews

"WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset", collected by pairing Wikipedia articles with a subgraph from the Freebase knowledge graph.(Luyu Wang et al, 2021)paper: https://t.co/FKmpfBARe8data: https://t.co/hS1xbWj9aI pic.twitter.com/HOQxRoc5we— WikiResearch (@WikiResearch) July 21, 2021

ThingFO v1.2's Terms, Properties, Relationships and Axioms - Foundational Ontology for Things / Luis Olsina https://t.co/c91oOm2SAg pic.twitter.com/3YxDhtG1iN— Aaron Bradley (@aaranged) July 21, 2021

Information Integration using the Typed Graph Model / Fritz Laux & Malcolm Crowe https://t.co/b3cAQt9c5U pic.twitter.com/fGm1V309Ul— Aaron Bradley (@aaranged) July 21, 2021

This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data…

Cf. Damion Dooley, @griffiemma, @plbuttigieg, FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration https://t.co/ARpniFL1FQ https://t.co/MXIfFbAeNc pic.twitter.com/qkHeMpcxQe— Aaron Bradley (@aaranged) July 21, 2021

In my previous post in which I discussed names, I also led in with the fact that I am a writer. Significantly, I did not really talk much about that particular assertion, because is in fact comes with its own rabbit hole quite apart from that associated with names and naming.

Zero-shot Visual Question Answering using Knowledge Graph https://t.co/R9VNiLFdZE pic.twitter.com/8TbY3lkgGu— Aaron Bradley (@aaranged) July 13, 2021

Similar Cases Recommendation using Legal Knowledge Graphs https://t.co/I9lTyMwsMF (yet another cc: for you @EmekaOkoye :) pic.twitter.com/Sqrm5uGhFF— Aaron Bradley (@aaranged) July 13, 2021

Using graphs, we can uncover interesting relationships for the SME to find similar patents and maybe uncover clusters or groups of patents…

Learn about a Google patent that enables searchers to explore connections between related entities in different types of media.

"We demonstrate that this approach significantly reduces the cognitive load required to users for visualizing and interpreting a knowledge graph...." > Pattern-based Visualization of Knowledge Graphs @lguspree et al. https://t.co/S1DuVfNlxc pic.twitter.com/EEH9o8A8eA— Aaron Bradley (@aaranged) July 7, 2021

SeaNet -- Towards A Knowledge Graph Based Autonomic Management of Software Defined Networks https://t.co/XZSHPF44Hj pic.twitter.com/p9MOGGxhB1— Aaron Bradley (@aaranged) July 6, 2021

Visual Question Answering (VQA) is concerned with answering free-form questions about an image. Since it requires a deep semantic and linguistic understanding of the question and the ability to...

How MUM helped improve access to high-quality COVID-19 vaccine information worldwide.

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.