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 ...

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.

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

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.

Posted by Natasha Noy, Research Scientist; and Omar Benjelloun, Software Engineer, Google Research There are tens of millions of datasets...

Check it. Explainable AI: From the peak of inflated expectations to the pitfalls of interpreting machine learning models https://t.co/AmS9dZz1Iv via @ZDNet & @linked_do #tech #digital #data #business pic.twitter.com/Lvxx7MTcsO— Kohei Kurihara -DataPrivacy for Fighting Covid-19- (@kuriharan) August 24, 2020

Understanding food recipe requires anticipating the implicit causal effects

We introduce Kensho, a tool for generating mapping rules between two

Graph Neural Networks (GNNs) are information processing architectures for

A quick introduction to 10 basic graph algorithms with examples and visualisationsContinue reading on Towards Data Science »

The index to the multiple installments in the 'Cooking with Python and KBpedia' (CWPK) series.

thirds of all clinical trials to find new…Continue reading on Medium »

authored by Intuit Distinguished Engineer and Architect, Jay Yu, Distinguished Engineer and Director, Kevin McCluskey, and Distinguished Data Scientist, Saikat Mukherjee.

world problems involving networks of transactions of various nature and social interactions and engagements are dynamic and can be modelled as graphs where nodes and edges appear over time. In this post, we describe Temporal Graph Network, a generic framework for deep learning on dynamic graphs.

Google has rolled out the new feature ‘People Card’ that enables business people or anyone who wants themselves to be easily identified. This feature is first rolled out in India, because of being the second largest internet market in the world. The feature is currently supported only in the English language for now, though other languages would be added in the future. The people card feature uses Google’s Knowledge Graph to display information provided by the user. The People card feature can be obtained by using your Google Account and by providing the mobile phone number.

defined meaning, better enabling computers and people to work in cooperation”. Since the publication of the paper the evolution of Semantic Web has moved its first steps with the representation of knowledge in forms of web standards. The following phase, more recently, is enabling a vast repertoire of applications with the emergence of machine learning methods, while maintaining the notion of knowledge with the aspects of graph: the Knowledge Graph (KG). 

sheets/ Best, Ryan submitted by /u/RyanAI100

Lee — the computer scientist best known as the inventor of the World Wide Web — himself who dreamt of a place full of readable data, neatly linked. Years later, we are working towards that goal, thanks to a vocabulary called Schema. This article tells you a bit more about how we got here.

In the Summer of 2019, the term “Knowledge Graph” (KG) suddenly appeared in the Gartner Hype Cycle for Emerging Technologies, already close to the peak of inflated expectation. That was quite a surprise, as it did not exist at all in the previous year’s: it just popped up halfway to the top, as a relevant...

taking app popping up every single week, it can be hard to decide which one is the best for your use case.