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This survey provides #knowledgegraph review: KG representation learning, knowledge acquisition & completion, temporal KG, KG #applications. It summarizes recent breakthroughs & perspective directions to facilitate future #research #AI #data h/t @aaranged

accessibility@cornell.edu for assistance.

world domain. A cursory Google search will result in

For the past year I have been doing a deep dive into when to apply graph technologies in a large fortune 10 healthcare company. I have…

This article provides a walk around the KBpedia knowledge graph and structure -- how to use it, what it does, and how to learn more about it.

Hey Dan, thanks for the ping. First of all, I'll point y'all to a related thread a few weeks ago... https://t.co/haTtBJfAhA 1/24— Aaron Bradley (@aaranged) February 25, 2019

If there's any doubts that Apple's Siri is (or at least leverages) a knowledge graph, they're laid to rest with this job posting from Apple > Siri - ML Engineer - Knowledge Graph - Apple (CA) https://t.co/1PFdecMk9V— Aaron Bradley (@aaranged) January 21, 2019

In your opinion which structured data markup syntax is the easiest to use when adding #schema.org information to a web page?— Aaron Bradley (@aaranged) January 29, 2019

The author of this Google doc, @jonoalderson, plans to make it "into a little website with structured/interlinked guidelines" but it's worth reading now > A general specification for implementing structured markup (using #schema.org and JSON-LD) https://t.co/CxnQLx7MNb— Aaron Bradley (@aaranged) January 28, 2019

This job posting from Microsoft provides some clues about where Satori is going - and by extension what we might expect to see in Bing. The extraction and curation of information "from data sources in public domains" is especially interesting. https://t.co/KtMt6Rrg2i pic.twitter.com/sVI1JE1WLd— Aaron Bradley (@aaranged) May 24, 2019

To help promoting the usage of @wikidata , here's another attempt to explain properties of statements with one of the most used qualifiers "start time" (pq:P850).Try it: https://t.co/tvOeWK7qBM#SPARQL #LinkedData pic.twitter.com/RshdPRx92D— Ivo Velitchkov (@kvistgaard) February 20, 2020

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Modeling_EN.md(Also available in French, by replacing EN by FR at the end of the URL)Trying to make a shorter answerAnd then I decided to make him a synthesis about the role of each feature …… and while writing this synthesis, I suddenly realized that these 3 features were all in connection with a problem of decompartmentalization !In fact, modeling paradigms often tend to compartmentalize the "things" ...... by

As I mentioned here before, Knowledge Graphs are the new Black! Even more important, they are a fundamental building block of a data driven enterprise ... 17 comments on LinkedIn

How to calculate TF-IDF in @Neo4j using only Cypher. TD-IDF is used in an #NLP pipeline to calculate the importance of a term within a document compared to a set of documents as a whole.Say you have a model of (:Document)-[:MENTIONS]->(:Term)1/— Adam Cowley (@adamcowley) April 6, 2019

#AI startup Adarga closed a £5M Series A #funding. Adarga allows organizations to transform normally data-intensive, human knowledge processes by analyzing vast volumes of #data. Adarga clients can build up a #KnowledgeGraph about subjects and targets

I would like to point to a crowd-funding of 📊 @rawgraphs, a project I find super interesting for a while and now they want to rewrite it. I think SPARQL and RAWGraphs can become best friends and so do they so help them getting there! https://t.co/VI0gK0ZZIS pic.twitter.com/UszINmFyuw— Adrian Gschwend (@linkedktk) October 2, 2019

“My interpretation of the W3C Graph Workshop wrap-up session today in Berlin. Sorry for the ones I left out, I focus on the ones I participated/understood, mostly around RDF. Feel free to contribute! Sessions/minutes are linked here: https://t.co/P3oV4Xshwr #W3CGraphWorkshop 👇”

Swiss EPFL's Blue Brain Nexus Project @bluebrainnexus released Nexus v1.0, which is from what I can see among others a SPARQL endpoint. I did not play with it yet but sounds like something to check out! https://t.co/y30L5thM44— Adrian Gschwend (@linkedktk) April 3, 2019

How to query #Wikidata (or any other #LinkedData endppoint) from within #rstats? @kala_karu explains. Documented code here: https://t.co/L9b8CEJWNu #tutorial #datascience #knowledgegraph #data #tech h/t @linkedktk @statistik_zh

consuming because experts are required to pick out biomedical inte

Tamara Louie | Data Scientist, Discovery

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The Ontologies Community of Practice is engaged in the development of ontologies for agricultural research. In a series of blog posts, we’ll take a look at ongoing ontologies projects and developments.

Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have devel...

#Knowledgegraphs are a natural fit for knowledge management: they model domains to retain more context & meaning even as information is parsed and abstracted for digital representation. Information is modeled in a way that is more intuitive & useful

Read the fifth and final installment of our blog series on artificial intelligence and the ways AI explainability adds context for credibility.

Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.

Karuna Pande Joshi, University of Maryland, Baltimore County You’re trailing bits of personal data – such as credit card numbers,

Deep learning is transforming the field of artificial intelligence, yet it is lacking solid theoretical underpinnings. This state of affair significantly hinders further progress, as exemplified by time-consuming hyperparameters optimization, or the extraordinary difficulties encountered in adversarial machine learning. Our three-day workshop stems on what we identify as the current main bottleneck: understanding the geometrical […]