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.

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

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...

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

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

A hands-on overview with a real world dataset

I wrote on this topic way back in 2016, but when a recent reader indicated that the original article didn't have images anymore (it happens), it seemed like a good opportunity to write about it again. I am Kurt Cagle, or, according to my birth certificate, Kurt Alan Cagle.

The increasing digitalization of the manufacturing domain requires adequate knowledge modeling to capture relevant information. Ontologies and Knowledge Graphs provide means to model and relate a...

Step by step examples for working with and evolving FIBO Vocabulary. Includes analysis of different option and a download file for the recommended approach.

This summer I've been mentoring two summer interns at Capgemini, Stian Teien and Andreas Mathisen. They have been working on a semantic knowledge graph...

The 2021 Knowledge Graph Conference, held online May 3–6, had over 1000 people attending. Special thanks to all of the 20+ people who…

A few slides on the applications of Graph Neural Networks https://lnkd.in/gyvkHrr...

Check out all the latest stories, product features and special promo offers from Careem.

This article is an introduction into a field of graph-based code analysis. We will discuss a base concept of graph-based code analysis and learn how to build a Codebase Knowledge Graph (or Code Knowledge Graph or simply CKG) for a .NET Core project using Strazh.

The success of neural network embeddings has entailed a renewed interest in using knowledge graphs for a wide variety of machine learning and information retrieval tasks. In particular, recent...

Using knowledge-infused learning to integrate knowledge graphs and machine learning can lead to improvements in autonomous driving. Six grand opportunities.

Fixing the talent pipeline so that finding rocket scientists doesn't have to be rocket science

Our e-book aims to shed light on what we believe is a real game-changer for those looking to improve upon simplistic answers sometimes arrived at by using traditional ML algorithms and approaches. We show how you are able to combine the power of both graphs and ML (in a variety of different ways) to help you arrive at better answers compared to using standard ML approaches alone.

Here I am trying to build a script that process the short scientific texts (abstracts) and finds Wikidata items corresponding to the terms. An interactive and editable table is also created to allow an editor to validate the found matches and find other related items. A bit amateurish attempt by a Wikidata newbie.

Iconology is a branch of art history that investigates the meaning of artworks in relation to their social and cultural background. Nowadays, several interdisciplinary research fields leverage...

Explainability techniques for Graph Neural Networks still have a long way to go compared to explanations available for both neural and decision decision tree-based models trained on tabular data....

Knowledge graphs are getting more mature and very practical in many different domains. From enabling data mesh architecture to disaster resilience, knowledge...