GraphNews

Excited for the next chapter! Vector completed its acquisition of MarkLogic and the baton is now in the hands of our new CEO Adrian Carr @ade_carr. Thank you to @GaryLBloom for your leadership over the past 8+ years. https://t.co/Z7AUQ4WcBa pic.twitter.com/CnEo6FZ8aU— MarkLogic (@MarkLogic) October 26, 2020

In this week's #twin4j, @mdavidallen teaches us all there is to know about super nodeshttps://t.co/VtYzHZNjvI#Neo4j pic.twitter.com/riYFmeHZmT— Neo4j (@neo4j) October 25, 2020

"Building #KnowledgeGraphs from Structured Sources".An explanation about the mapping approach (and languages) adopted to integrating heterogeneous data.My new article/tutorial for @TDataScience.#rml #jarql #tarql #r2rml #dataintegration #SemanticWebhttps://t.co/YwgIGupHr3 pic.twitter.com/qAyzzX3VMf— Giuseppe Futia (@giuseppe_futia) October 28, 2020

KnowID: An Architecture for Efficient Knowledge-Driven Information and Data Access / Pablo Rubén Fillottrani & C. Maria Keet 1/2 https://t.co/WBsNQmsIXJ pic.twitter.com/G6drmpmccN— Aaron Bradley (@aaranged) October 27, 2020

Created a #3D #MindMap of people who inspired Albert Einstein and who were inspired by Albert Einstein with a #SPARQL query from #WikiData. The #SPARQL query can be found at #github https://t.co/bJEBujXcFw, the live demo at https://t.co/5dgucBrn8y pic.twitter.com/wd7DoB6kjW— Ingo Straub (@inforapid) October 29, 2020

“Graph data science and graph analytics reveal the workings of intricate systems and networks at massive scale.”Download your free copy of Graph Data Science For Dummies: https://t.co/io3Hc7I37y#GraphDataScience #DataScience #ML pic.twitter.com/Bdyt7ChHqr— Neo4j (@neo4j) October 29, 2020

To quickly understand tabular data, EURECOM and Orange are developing the DAGOBAH semantic annotation platform.

Debrief from AstraZeneca’s Data Science and Artificial Intelligence

Great news everybody, there are no limitations regarding the usage of yEd Live anymore! It is free to use for everybody and even in commercial environments...

A knowledge graph captures the semantics of a particular domain using a set of definitions of concepts, their properties, relations between them, and logical constraints that are expected to hold. Knowledge graphs consolidate and integrate an organization’s information assets and make them more readily available to all members of the organization. There are many applications and use cases that are enabled by knowledge graphs. Information from disparate data sources can be linked and made accessible for to answer questions you may not even have thought of yet. Information and entities can be...

Company Achieves “Industry First” Results in New Graph Database Performance Benchmark

New website of oorlogsbronnen.nl about WWII in the Netherlands is launched today. Congratulations to Lizzy Jongma and her team with this impressive achievement...

Discover how a Product Knowledge Graph can help you create an immersive e-commerce experience and sell more products.

The Austrian provider of knowledge graph and text mining technology Semantic Web Company has announced the opening of its new U.S. office in Boston.

Graph neural networks (GNNs) have become a popular approach to integrating structural inductive biases into NLP models. However, there has been little work on interpreting them, and specifically...

Are you evaluating enterprise knowledge graphs (EKGs) for your business? This was the deck of a talk I gave for the AI+Knowledge Graph conference held ...

One place to keep up with all your information sources. With Inoreader, content comes to you, the minute it's available. Subscribe to RSS Feeds, Blogs, Podcasts, Twitter searches, Facebook pages, even Email Newsletters! Get unfiltered news feeds or filter them to your liking.

What’s advancing the world of graph databases, and what’s slowing us down?

My engineering friends often ask me: deep learning on graphs sounds great, but are there any real applications? While Graph Neural Networks are used in recommendation systems at Pinterest, Alibaba and Twitter, a more subtle success story is the Transformer architecture, which has taken the NLP world by storm. Through

The metaphactory platform enables knowledge workers to create and gain meaningful insight into their data with one comprehensive software solution.

Learn how DeepWalk treats creating graph embeddings as equivalent to creating word embeddings

Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering https://t.co/AdDke9AtZ0 pic.twitter.com/QXPucOK1Xo— Aaron Bradley (@aaranged) September 3, 2020

Great job to Prasun Gera for presenting our joint research on Traversing Large #Graphs on #GPUs with Unified Memory, with Hyojong Kim, @piyusch, & Hyesoon Kim, in virtual Tokyo @VLDB2020 #DataScience @NJIT @NJITYingWu https://t.co/J7V4K94VSF pic.twitter.com/LjsrKrqHJY— David Bader (@Prof_DavidBader) September 7, 2020

We got this year's @AmazonScience AWS ML Award for our work with @befcorreia on #protein design using #geometricdeeplearning Will help to take #masif to the next level https://t.co/Ec7t2g7nqV pic.twitter.com/OrHGwHp1cE— Michael Bronstein (@mmbronstein) September 9, 2020

"PNEL: Pointer Network based End-To-End Entity Linking over Knowledge Graphs." with an evaluation over three datasets on the #Wikidata Knowledge Graph.(@debayan Banerjee et al, 2020)https://t.co/cTCq4EhrGP pic.twitter.com/Ci1yn2CPDp— WikiResearch (@WikiResearch) September 8, 2020

Some good progress happening on the RDF* mailing list, towards a de-facto standard for representing statements about statements in a user-friendly syntax. See whole thread for context if interested https://t.co/S6N9w3XLH7— Holger Knublauch (@HolgerKnublauch) September 7, 2020