Great Ben Lorica (@bigdata) podcast interview with @kejriwal_mayank about knowledge graphs. I had waited years to hear Ben mention "RDF" on his podcast.The buzzphrase "knowledge graphs" has become a foot in many doors for this set of W3C standards!https://t.co/jkBg5w7Pxj— Bob DuCharme (@bobdc) October 17, 2020
Our #EMNLP2020 paper introduces MHGRN, a multi-hop #GraphNeuralNetworks model that can answer complex questions via relational reasoning over #KnowledgeGraphs. Kudos to our excellent summer interns, Yanlin and Xinyue. @xiangrenNLP @nlp_usc Paper: https://t.co/8KzsbrL0pw [1/3] pic.twitter.com/x1oi4tQwRK— Yuchen Lin (@billyuchenlin) October 20, 2020
Guess which one might be the geometric space of choice for geometric representation learning with graphs? Keynote by Maximilian Nickel at #cssa2020 @cikm2020 https://t.co/EL3FgSRnpw pic.twitter.com/1PmlzkKZhD— Harald Sack (@lysander07) October 20, 2020
Can JSON Schema can be used to define and validate JSON-LD? "think the answer is a qualified 'yes', says @philbarker. "Here’s a proof of concept; do me a favour and let me know if you think it is wrong." https://t.co/pnGD4UQYFd— Aaron Bradley (@aaranged) October 20, 2020
How Does AI Understand Graphs?time is technically a graphhttps://t.co/iRlwXdV0g1#ai #graphtheory #graphdatabases #timeseries pic.twitter.com/ByNmkqC3DW— Graph Day (@GraphDay) October 19, 2020
Got a beef with you @aarontay: through one of your tweets I've discovered the existence of Ashleigh Faith's "IsA DataThing" YouTube channel on information architecture & semantics, and now I need to watch 31 videos :) https://t.co/Z3IcOlSdoS pic.twitter.com/wExS2xKLAi— Aaron Bradley (@aaranged) October 19, 2020
Intel and Katana Graph Team on Large-scale Graph Analyticshttps://t.co/W1C6jqsZk4@KatanaGraph #graphanalytics #analytics #graphdatabase pic.twitter.com/cazSPRV60c— Graph Day (@GraphDay) October 19, 2020
Just published by @WikimediaIL :https://t.co/JadkTTL6cJCould this be the best #SPARQL / @wikidata query tutorial ever? pic.twitter.com/yeyRum76ix— WikiCite (@Wikicite) October 21, 2020
Our mission of bringing order to chaos of distributed and unstructured data continue! In this blog, @VlastaKus shows how to convert text into a meaningful knowledge graph by extracting entities and relationships automatically from text. https://t.co/LwcHk7G2vK— Alessandro Negro (@AlessandroNegro) October 21, 2020
Bias in Conversational Search: The Double-Edged Sword of the Personalized Knowledge Graph @emmagerritse @fhasibi @arjenpdevries https://t.co/ELFJc17XLv pic.twitter.com/bexlxYBu6D— Aaron Bradley (@aaranged) October 21, 2020
Large Scale Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training @agarwal_oshin et al. https://t.co/pwU6F1vHmr pic.twitter.com/6Nqy6RiU4h— Aaron Bradley (@aaranged) October 27, 2020
Check out the new issue of https://t.co/UWeN9c7tgC. Content focused on #BigData #Covid19 #datagovernance #EDM #knowledgegraphs more. Great authors this month - @georgefirican Polikoff of @TopQuadrant @DGPROS Mecca @thinkdataworks @craigmullins @RSeiner.https://t.co/UWeN9c7tgC pic.twitter.com/DbZVQbmJGH— Robert S. Seiner (@RSeiner) October 22, 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
Semantics of the Black-Box: Can knowledge graphs help make deep learning systems more interpretable and explainable?https://t.co/ilcnQQcIhYby Manas Gaur et al.#KnowledgeGraph #DeepLearning— arXiv Daily (@arXiv_Daily) October 26, 2020
Excited for the next chapter! Vector completed its acquisition of MarkLogic and the baton is now in the hands of our new CEO Adrian Carr @ade_carr. Thank you to @GaryLBloom for your leadership over the past 8+ years. https://t.co/Z7AUQ4WcBa pic.twitter.com/CnEo6FZ8aU— MarkLogic (@MarkLogic) October 26, 2020
In this week's #twin4j, @mdavidallen teaches us all there is to know about super nodeshttps://t.co/VtYzHZNjvI#Neo4j pic.twitter.com/riYFmeHZmT— Neo4j (@neo4j) October 25, 2020
"Building #KnowledgeGraphs from Structured Sources".An explanation about the mapping approach (and languages) adopted to integrating heterogeneous data.My new article/tutorial for @TDataScience.#rml #jarql #tarql #r2rml #dataintegration #SemanticWebhttps://t.co/YwgIGupHr3 pic.twitter.com/qAyzzX3VMf— Giuseppe Futia (@giuseppe_futia) October 28, 2020
KnowID: An Architecture for Efficient Knowledge-Driven Information and Data Access / Pablo Rubén Fillottrani & C. Maria Keet 1/2 https://t.co/WBsNQmsIXJ pic.twitter.com/G6drmpmccN— Aaron Bradley (@aaranged) October 27, 2020
Created a #3D #MindMap of people who inspired Albert Einstein and who were inspired by Albert Einstein with a #SPARQL query from #WikiData. The #SPARQL query can be found at #github https://t.co/bJEBujXcFw, the live demo at https://t.co/5dgucBrn8y pic.twitter.com/wd7DoB6kjW— Ingo Straub (@inforapid) October 29, 2020
“Graph data science and graph analytics reveal the workings of intricate systems and networks at massive scale.”Download your free copy of Graph Data Science For Dummies: https://t.co/io3Hc7I37y#GraphDataScience #DataScience #ML pic.twitter.com/Bdyt7ChHqr— Neo4j (@neo4j) October 29, 2020
Great news everybody, there are no limitations regarding the usage of yEd Live anymore! It is free to use for everybody and even in commercial environments...
Knowledge Graphs - Amazon Neptune - Amazon Web Services
A knowledge graph captures the semantics of a particular domain using a set of definitions of concepts, their properties, relations between them, and logical constraints that are expected to hold. Knowledge graphs consolidate and integrate an organization’s information assets and make them more readily available to all members of the organization. There are many applications and use cases that are enabled by knowledge graphs. Information from disparate data sources can be linked and made accessible for to answer questions you may not even have thought of yet. Information and entities can be...
New website of oorlogsbronnen.nl about WWII in the Netherlands is launched today. Congratulations to Lizzy Jongma and her team with this impressive achievement...
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
Graph neural networks (GNNs) have become a popular approach to integrating structural inductive biases into NLP models. However, there has been little work on interpreting them, and specifically...
