GraphNews

Presentation for Data Day Texas / Global Graph Summit 2019

SciBite CSO and Founder Lee Harland shares his views on the use of BERT (or more specifically BioBERT) for deep learning approaches.

Read this interview with Ivan Zoratti – the former Chief Technology Officer of MariaDB – and learn why he joined Neo4j as the Director of Product Management.

The United States is in the midst of an opioid epidemic with recent estimates indicating that more than 130 people die every day due to drug overdose. The over-prescription and addiction to opioid...

#data stored in graphs mimic the way humans understand information. @ontotext built a Star Wars #Knowledgegraph using RDF. But…what do #software developers want? Many APIs are built using #GraphQL #JSON. “A query language for your API” #GraphDB #database

Today we want to make this available in a first release under an Apache License for you to try out and test. It works with Neo4j from 3.4.x

A Practical Guide to Build an Enterprise #KnowledgeGraph for Investment Analysis. 1. Schema Design 2. D2R Transformation 3. Information Extraction 4. Data Fusion with Instance Matching 5. Storage Design and Query Optimization

A refresher on the Google Knowledge Graph and how you can find facts about people, places and things in knowledge panels on Search.

driven social media company, it is essential to pursue a basic CRUD (Create, Read, Update, Delete) operation to add more people, add new messages to the current database or find associated information. This helps the company figure out a certain user’s profile. For example, it might find that user Jeff has many posts relating to AI and music. Thus we may conclude him being a programmer, and so on. Sometimes requirements for one analysis can be extremely tricky. For example, you might have a query for Find all posts from users and count the number of posts up to 3 levels down [1].

A quick summary of my(and many other) talks at KGC-2019

walk or mapping.

This page describes our functional and technical approach to constructing schema.org markup.

Deep learning models on graphs have achieved remarkable performance in

This paper is a survey of the research topics in the field of Semantic Web, Linked Data and Web of Data. This study looks at the contributions of this research community over its first twenty years of existence.

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