Nicole Buckenwolf use ontologies and taxonomies to organize the product information that you see at businesses like Amazon and Etsy.

Drivine - Graph Database Client for Node.js & TypeScript

What if two of the hottest graph frameworks come together? You better come to the party! Leverages the flexibility of GraphQL in the frontend with the ... 16 comments on LinkedIn

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

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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...

Knowledge graph applications are one of the most popular graph use cases being built on Amazon Neptune today. Knowledge graphs consolidate and integrate an organization’s information into a single location by relating data stored from structured systems (e.g., e-commerce, sales records, CRM systems) and unstructured systems (e.g., text documents, email, news articles) together in a […]

Ontotext has released GraphDB 9.6 that implements a long list of usability improvements collected as input over various channels.

Amy Hodler is Director, Analytics and AI Program at Neo4j   Conventional anti-money laundering (AML) analytics fail to detect the hidden relationships that reveal criminal networks, says Neo4j’s Amy Hodler Catching money launderers is a huge and growing challenge. Criminal money laundering activities are often hidden in plain sight, within legitimate transactions. Money laundering now […]

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 #Neo4j...

Nebula Graph 2.0 GA is here! Following hard work for nearly one year and several beta versions, Nebula Graph 2.0 is now generally available and can be ...

Getting a graph database to be performant and easy to use is very different from making a NoSQL (non-relational) database high-performing. Listen in as Todd Escalona of AWS talks with Marc Wangenheim, Senior Engineering Manager at Nike, about how the company powers a number of applications via a social graph, built on Amazon Neptune, which […]

This demo allows hands-on experience on Knowledge Graph databases by executing SPARQL queries side-by-side with their SQL counterparts.

“…And that’s why graph databases are so cool,” I say, after droning on for some time. “You get it, right?”

Announcing Stardog Explorer, a brand new way to easily explore the connections in your data. Powerful, intuitive new visualization and search capabilities make it easier for more types of users to benefit from your connected data in Stardog.

Mike Tung: "I want to propose a much simpler statement of the benefits of knowledge technologies. KG technologies are indeed useful, but the most productive... 30 comments on LinkedIn

TerminusDB has raised $4.3 million to build what it calls the "knowledge collaboration infrastructure" for the internet.

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 →