GraphNews

As requested , here are a few non-exhaustive resources I'd recommend for getting started with Graph Neural Nets (GNNs), depending on what flavour of learning suits you best. Covering blogs, talks, deep-dives, feeds, data, repositories, books and university courses! A thread 👇 pic.twitter.com/el1kb8rS4G— Petar Veličković (@PetarV_93) September 17, 2020

You see these great looking Google results? The ones with all the bells and whistles? These are called rich results and you can get them too!

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

Graphs are a natural and fundamental representation of describing the activities, relationships, and evolution of various complex systems. Many domains such as communication, citation,...

Google introduces a personalized entity repository, similar to a user-specific knowedge graph to predict actions and suggestions for users of Google.

Interview with Giovanni Campagna, one of the Almond principal developers

Get this introductory book on graph databases to learn the basics of the fastest-growing database technology and get started on your own graph project.

Ontotext has released the 9.4 version of GraphDB with the main objective to lower the cost of creating and consuming knowledge graphs. Read further.

Use KronoGraph, the time visualization toolkit for JavaScript developers, to build interactive, scalable timeline tools to explore evolving relationships and events.

I’m Azeem Azhar. I convene Exponential View to help us understand how our societies and political economy will change under the force of rapidly accelerating technologies. Some of my latest commentary: A short history of knowledge technologies How the roadmap for self-driving cars has led them up a blind alley

Using Python to create a graph in Neo4j based on real-world trade data we derive insights around trading behavior of different regime types

Apple Search Starts with Siri Search In 2012, I wrote about the Apple Siri Patent application. The patent I wrote about was Intelligent Automated Assistant. In coming out with Siri, an automated assistant, Apple was creating something much more complex than just a search engine. As the patent filing says: Unlike search engines which only […]

Just launched TerminusHub on Hacker News. Would really appreciate upvotes - in the 'Show HN' section. TerminusHub, Revision Control for Structured Data...

Walder offers an easy way to set up a website or Web API on top of decentralized knowledge graphs. - KNowledgeOnWebScale/walder

As easy to use as a word document or bulleted list, and as powerful for finding, collecting, and connecting related ideas as a graph database. Collaborate with others in real time, or store all your data locally.

All right, I'll admit, this is clickbait. I generally avoid writing "[Fill in Ordinal Number of Bullet Points Here] [Cool|Neat|Amazing|Similar Token] [List of X Thing]" articles, because they usually have no real value to them, but just for once, given the subject matter, I'll succumb to the temptat

Category Theory and Functional Programming If you are into graph databases - you need to check out category theory. It is going to be a 'thing'. The ...

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The debate between two divergent schools of thought in the underlying architecture of AI systems is starting to ask a new question: Why not both?

More is not Always Better: The Negative Impact of A-box Materialization on RDF2vec Knowledge Graph Embeddings - Andreea Iana, @heikopaulheim https://t.co/ZlN50kgXrk— Aaron Bradley (@aaranged) September 2, 2020

Our #Yahoo! Knowledge Graph version of #Wikipedia entity embedding is now publicly available. This will be the version we use to trigger the related entity search for knowledge panels in Yahoo! Search, try it if you need general entity embedding in any task. @wikiworkshop https://t.co/eB9H6ai2zI— Chien-Chun Ni (@saibalmars) September 2, 2020

"VisualSem: a high-quality knowledge graph for vision & language", based on #Babelnet and #Wikipedia(Alberts et al, 2020)https://t.co/mWNh7QxXpZ@claravania#NLProc #ComputerVision pic.twitter.com/s8bGn6MAdV— WikiResearch (@WikiResearch) September 3, 2020

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👋 Hello, I hope you are all doing well during the lockdown.

based diagnosis of disease, and drug repurposing. Integrating data and knowledge is a formidable challenge in biomedical research. Although new scientific findings are being discovered at a rapid pace, a large proportion of that knowledge is either locked in data silos (where integration is hindered by differing nomenclature, data models, and lice

In this post, we look at the new visualization features recently added to the Amazon Neptune workbench and released on August 12, 2020. These additional capabilities allow you to produce an interactive graph diagram representing the results of your Gremlin and SPARQL queries. We look at some Gremlin-specific features and then do the same for SPARQL. Finally, we look at some of the more advanced ways you can modify the visualizations. As a sidenote, this entire post was produced using the workbench.

This open access book covers all facets of entity-oriented search—where “search” can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent an

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.