Over the recent years, Graph Neural Networks have become increasingly popular in network analytic and beyond. With that, their architecture noticeable diverges from the classical multi-layered...

With the Open Research Knowledge Graph (https://orkg.org) developed by TIB – Leibniz-Informationszentrum Technik und Naturwissenschaften and L3S Research...

Stanford / Winter 2021

Wireframing/interface design and user experience flow definition activities are a powerful tool to visualize knowledge graph applications.

Algorithms have been fundamental to recent global technological advances and, in particular, they have been the cornerstone of technical advances in one field rapidly being applied to another. We...

This paper, originally written in Hungarian by Dénes Kőnig in 1931, proves that in a bipartite graph, the minimum vertex cover and the maximum matching have the same size. This statement...

"Relational world knowledge representation in contextual language models: A review" Knowledge bases such as #Wikidata provide a high standard of factual precision which can in turn be expressively modeled by language models.(Safavi and Koutra, 2021)https://t.co/zZuhjIvCva pic.twitter.com/NCLBQBlLPL— WikiResearch (@WikiResearch) April 23, 2021

In this blog post, @ABrokenJester discusses how #RDFstar & #SPARQLstar can make provenance tracking in #RDF #KnowledgeGraphs easier, & demonstrates how RDF-star annotations can be retrieved, displayed & visualized graphically in #metaphactory: https://t.co/qbdXJvBlOp— metaphacts (@metaphacts) April 26, 2021

Network Analysis, Topic Modeling, and a Wordcloud!

Knowledge graphs bring vital changes to connected inventories for financials and enable them to save much time and expenses

Google shows us how automated data wrappers may be used to extract entity information from web pages and make The knowledge graph better.

I recently purchased a new laptop one with enough speed and space to let me do any number of projects that my nearly four-year-old workhorse was just not equipped to handle.

We are excited to announce the launch of HealthECCO, a non-profit association that builds on the amazing work of the CovidGraph Project. The core CovidGraph Neo4j Graph, applications and community were built by a loose collection of volunteers, enthusiasts and organisations. Setting up HealthECCO will allow us to build a more robust operating environment for […]

SPARQL is a powerful language for working with RDF triples. However, SPARQL can also be difficult to work with, so much so that it often is not utilized anywhere near as often for its advanced capabilities, which include aggregating content, building URIs, and similar uses.

13 months ago we released a JavaScript based SHACL implementation for validating RDF. Today I'm happy to announce our version of the SHACL playground, implemented by our @zazukocom colleague @tpluscode 🚀100% client side in your browser, try it out here https://t.co/N7cWtG1LW0 pic.twitter.com/OuJUKkJfjG— Adrian Gschwend (@linkedktk) May 1, 2021

How simple structured data trumps clever machine learning

Why Question-Answering Engines? The search only for documents is outdated. Users who have already adopted a question-answering (QA) approach with their personal devices, e.

For regular readers of the (lately somewhat irregularly published) The Cagle Report, I've finally managed to get my feet underneath me at Data Science Central, and am gearing up with a number of new initiatives, including a video interview program that I'm getting underway as soon as I can get the l

In late November the U.S. Federal Drug Administration approved Benevolent AI’s recommended arthritis drug Baricitnib as a COVID-19…

Of course, every thing “isa” thing

On the role of knowledge that is structured, explicit and intelligible in providing a path toward higher machine intelligence

The future of search is the rise of intelligent data and documents. Way back in 1991, Tim Berners-Lee, then a young English software developer working at CERN…

Is it me or the Twitter graph and the LinkedIn graph feel a bit disconnected? I personally tend to interact more with the first and that's why I have the impression that the second might be missing out on some of the nice and "graphy" content that I've been producing lately. This article is just a c

Building scalable semantic retrieval from image, text, graph, and interaction data

I worked on some experiments on RDF-to-text generation. The goal is to generate coherent multi-sentence texts from data in a knowledge graph. While not...

AmpliGraph is a TensorFlow-based open-source library developed by Accenture Labs for predicting links between concepts in knowledge graphs.

Version 5 is now live…

DIG: Dive into Graphs A research-oriented library that includes unified and extensible implementations of algorithms for (1) graph generation, (2) self-supervised...