A collection of important graph embedding, classification and representation learning papers with implementations. - benedekrozemberczki/awesome-graph-classification

Discover the top 5 graph analytics takeaways from Gartner's Data & Analytics Summit, from creating context to improving communication.

Stanford / Winter 2021

Hierarchical Graph Neural Networks - Over the recent years, Graph Neural Networks have become increasingly popular in network analytic and beyond. With...

Alan Morrison's answer: You’re not generating a graph as much as you are seeding, nurturing, harvesting and consuming one. You’re putting in place a cyclical, organic process to allow the graph to grow, become useful, evolve, thrive, and—ideally—marry up with other graphs, the combination of whic...

How simple structured data trumps clever machine learning

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

Basic Introduction to what Graph Analytics is…

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

A Knowledge Graph for the Agri-Food Sector @rapw3k https://t.co/Uko5uhcg2F— Aaron Bradley (@aaranged) February 1, 2021

Bias in ontologies - a preliminary assessment / C. Maria Keet https://t.co/x1VaU9yX4R 2/2 pic.twitter.com/pdeyXdmFZs— Aaron Bradley (@aaranged) January 21, 2021

Building and Using Personal Knowledge Graph to Improve Suicidal Ideation Detection on Social Media https://t.co/pLMXCgQOEx pic.twitter.com/xnt1jhcmdE— Aaron Bradley (@aaranged) December 17, 2020

We kicked off our #NeurIPS2020 series joined by @TacoCohen, ML Researcher at @Qualcomm @Qualcomm_Tech, to discuss his current research in equivariant networks and video compression using generative models, as well as his paper “Natural Graph Networks.”— The TWIML AI Podcast (@twimlai) December 22, 2020

A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources https://t.co/JsMcHN8Z6g pic.twitter.com/IxbRmK4ioo— Aaron Bradley (@aaranged) December 8, 2020

For the last few years, I have been promoting the idea of the Hardware Graph. My assertion was that graph hardware needs a focus on simple…

"Inrupt ... has launched its first enterprise-ready Solid servers for use by more than a dozen partners, including the NHS, the BBC and NatWest Bank." https://t.co/HcW0uWJjUZ— Aaron Bradley (@aaranged) November 10, 2020

Can’t wait to get my copies as well. This has been a long time in the works so glad it’s finally come to fruition. https://t.co/kput7PAJg1 https://t.co/yqMFwmjD92— Dave Bechberger (@bechbd) October 27, 2020

Speaking of personalized knowledge graphs....Knowledge Graphs to Empower Humanity-inspired AI Systems @hemant_pt, Valerie Shalin, @amit_p https://t.co/7gYiAxNHhU pic.twitter.com/bVccm8IxCK— Aaron Bradley (@aaranged) September 16, 2020

This "Load balance graph queries using the Amazon Neptune Gremlin Client" blog post is a nice body of work covering a more advanced topic than is typically seen in the TinkerPop community. https://t.co/4mJVRxENwL #graphdb pic.twitter.com/d94tOwUaQB— stephen mallette (@spmallette) September 17, 2020

“How do you select a graph database? Learn how in @itworldca. Read here: https://t.co/Z529PWdeW6 | #GraphDatabase #GraphDB #GraphAnalytics #DataScience #Developer #Analytics #BigData”

TopQuadrant CEO, Irene Polikoff, provides an overview of the two main graph models along with illustrations of their similarities and differences in graph diagrams in Part I of II in this article series from @TDAN_com https://t.co/CxOrTb3ELL#knowledgegraphs #datagovernance— TopQuadrant (@TopQuadrant) September 25, 2020

I'll be discussing "Graph Queries with Gremlin Language Variants" at the Category Theory and Applications group meetup on October 6: https://t.co/MG1HpNEiGd Be prepared to see Gremlin in many different forms! #graphdb pic.twitter.com/OIOsfLvWze— stephen mallette (@spmallette) September 28, 2020

Technology research and analyst house Bloor Research places Ontotext as champion among RDF graph providers in its latest update on the graph database market

Graph Databases are a great solution for many modern use cases: Fraud Detection, Knowledge Graphs, Asset Management, Recommendation Engines, IoT, Permission Management … you name it.  All such projects benefit from a database technology capable of analyzing highly connected data points and their relations fast – Graph databases are designed for these tasks. But the nature of graph data poses challenges when it comes to *buzzword alert* scalability. So why is this, and are graph databases capable of scaling? Let’s see... In the following, we will define what we mean by scaling, take a closer look at two challenges potentially hindering scaling with graph databases, and discuss solutions currently available. What Is the “Scalability of Graph Databases”? Let’s quickly define what we mean here by scaling, as it is not “just” putting more data on one machine or throwing it on various ones. What you want when working with large or growing datasets is also an acceptabl

Photo by AndreyPopov on iStockWe all use the Google Knowledge Graph tens of times a day, but maybe not many of us are aware to be actually querying the Graph while making a simple search on Google.When you search for something, for example, “Goldman Sachs”, what you get is a list of snippets of web pages plus an Infobox next to the search results.The Knowledge Graph behind your Google search allows to enhance the search engine with specific and possibly useful features on the “entity” you are looking for (in this case Goldman Sachs), gathered from a variety of sources. So, allegedly, Google Knowledge Graph enhances the result of our search with semantics [4].Let’s now try to consider reasoning.Now, say we are studying Goldman Sachs for some reason and we wish to know whether there is some person x in Goldman Sachs board who is the CEO of some other company y that is in the Tech field?Or in other terms, in a ‘fancy’ logic conjunctive query fashion:∃ x y board(Goldm

https://douroucouli.wordpress.com/2019/05/10/obographviz-0-2-2-released-now-with-visualization-of-equivalence-cliques/