The field of Graph Neural Networks has matured substantially and here I propose to have a look at the top applications of GNNs.

Discover the new features in GDS 1.5, including new algorithms, more machine learning, and easier production deployment.

A provoking claim As a software anarchitect, I like to challenge the status quo: I propose to use RDF and SPARQL for the core domain logic of business applications. Many business applications consist of simple workflows to process rich information. My claim is that RDF and SPARQL are ideal to model and process such information while a workflow engine can orchestrate the processing steps. Cheap philosophy Algebraic data types are concrete structures capable of representing information explicitly and are becoming popular for domain modeling. But also a logical framework like RDF shines at rep...

Large amounts of threat intelligence information about mal-ware attacks are available in disparate, typically unstructured, formats. Knowledge graphs can capture this information and its context...

Cyber threat and attack intelligence information are available in non-standard format from heterogeneous sources. Comprehending them and utilizing them for threat intelligence extraction requires...

Recommender systems are an essential component of e-commerce marketplaces, helping consumers navigate massive amounts of inventory and find what they need or love. In this paper, we present an...

Demo of COMeT, a knowledge base construction engine that learns to produce new nodes and connections in commonsense knowledge graphs, on ATOMIC and ConceptNet.

Contextual advertising provides advertisers with the opportunity to target the context which is most relevant to their ads. However, its power cannot be fully utilized unless we can target the...

Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback. These systems...

Knowledge graph embedding methods learn embeddings of entities and relations in a low dimensional space which can be used for various downstream machine learning tasks such as link prediction and...

Our #Neo4j sandbox infrastructure got a big update. And with this there are all new versions of Neo4j, APOC, Graph Data Science, Bloom and Neosemantics available for you to learn and explore. Enjoy the new sandboxes and let us know what you think.https://t.co/HVLpAtVQ2y— Neo4j (@neo4j) February 19, 2021

Hi everyone, Our video this week is an interview with NASA’s David Meza from Ashleigh Faith’s IsADataThing YouTube channel. Jesús Barrasa analyses the structured data of the White House website, Clair Sullivan imports data from Python, and I show how… Read more →

THREAD - how you can do crazy cool things with @Neo4j and Graph Data Science (GDS). This thread is going to be a walk-through example of what you can do, and how you can even found a startup on the back of this stuff.First, some background on my data: pic.twitter.com/aT6enmV5SC— 𝔻𝕒𝕧𝕚𝕕 𝔸𝕝𝕝𝕖𝕟 (@mdavidallen) February 23, 2021

Tracing the triumphs and challenges of two decades of Semantic Web research and applications.

Basic Introduction to what Graph Analytics is…

Graph databases are the fastest-growing category in all of data management. Here's how to pick one.

The Stardog 7.6.0 release can load data at million triples per second speed.

Read about how knowledge graphs can unlock meaning and thus create a smart future-proof living repository of scientific data and its relationships.

Learn what graphs, the graph theory, and graph databases are in this week’s #GraphCast, featuring two slick videos explaining these concepts.

This blog highlights some of the new automation features that Cambridge Semantics is building into our scalable knowledge graph platform - Anzo.

Sign in or join now to see posts like this one and more.

The Future is Big Graphs! A very worthwhile read on the impact big graphs will bring to data processing pipelines. https://lnkd.in/gww-KSw...

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.

Although artificial intelligence capabilities are improving daily, it is not always easy to put the AI rubber on the road – especially when it comes to understanding AI’s contextual data and problem-solving approaches. How about bringing in some “real” intelligence? Graphs are a typically human way

The largest funding round to date in the graph market is good news not just for TigerGraph, but for the market at large

Knowledge graphs: The secret of Google Search and now XDRhttps://t.co/kZOvSz3Kke#Infosec #Security #Ceptbiro #Cybersecurity #KnowledgeGraphs #GoogleSearch #XDR— Rene Robichaud (@ReneRobichaud) February 17, 2021