GraphNews

In this blog post, we explore how and why semantics and graph data models are necessary when implementing a data fabric architecture.

Short comparision of #SPARQL and #GraphQL by @RubenVerborgh. One SPARQL Query can go against multiple SPARQL endpoints in a natural way - that is not equal to schema stitching in GraphQL because there is no need for schema assumptions of different #API's: https://t.co/RWYuvBSIqX— Francis Opoku (@fraopo) December 23, 2018

A big new #LOAD resource: https://t.co/J44j8EKsGo All 500M+ owl:sameAs statements in the #LOD cloud, their closure into 50M equivalence classes, and an estimated error degree for all of these. All for download at https://t.co/sKeetxXzgY— Frank van Harmelen (@FrankVanHarmele) April 28, 2019

Combines graph and document technologies, ontology design, and AI data science expertise

Grab your free copy of the brand new O'Reilly book, "Graph Algorithms: Practical Examples in Apache Spark & Neo4j" – a practical guide to graph analytics.

I believe that within five years there will be a dramatic growth in a new field called Knowledge Science. Knowledge scientists will be ten…

Who, what, when, where, how of anything and everything dressed in metadata with Margaret Warren of ImageSnippets and ... and a Porsche art car.

How AI is evolving towards custom graph hardware

From a bird eye's view, the DBpedia Extraction Framework takes a MediaWiki dump as input, and turns it into a knowledge graph. In this talk, I discuss the crea…

Generating structured #KnowledgeGraphs is relevant for decision making & information augmentation. #research studies generating KGs as relational representation of inputs: nodes represent entities, edges represent relations #EmergingTech #AI h/t @aaranged

The mission of FKG group is to create specifications for encoding ontologies that AI Assistants can operate upon enabling them to execute functions embedded in a web page. FKGs are encoded in JSON-LD, this group defines the vocabulary. A detailed proposal can be found at: https://github.com/keyvan-m-sadeghi/assister/blob/assister-conception/rfcs/text/assister-conception/README.md

Augmented analytics, continuous intelligence and explainable artificial intelligence (AI) are among the top trends in data and analytics technology that have significant disruptive potential over the next three to five years, according to Gartner, Inc.

Gartner Names PoolParty as Visionary in Metadata Management Magic Quadrant. Our modern approach combining machine learning and knowledge graphs makes the difference!

Published on February 22, 2020 3:28 AM GMT

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Joshua Shinavier from Uber coming up with a broad definition of knowledge graphs #us2ts2019 pic.twitter.com/0LbMMJQP6S— Gaurav Vaidya (@mrvaidya) March 11, 2019

As a follow up of word embedding post, we will discuss the models on learning contextualized word vectors, as well as the new trend in large unsupervised pre-trained language models which have achieved amazing SOTA results on a variety of language tasks.

passing neural networks (MPNNs) have been successfully applied to

So you have heard the hype about knowledge graphs? How can Pythonistas join forces with Fashionistas to form an authoritative single source of truth for fashion e-commerce, benefiting applications such as Search, Discovery, and Personalisation. This talk will give you a unique insight into how knowledge graphs can provide powerful ways to analyse and emphasise relationships in data. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analys...

Do you want to learn more about #knowledgegraphs and data-centric architecture? @AlanMorrison put together a list of resources #datacentric #dataarchitecture #semantics #LinkedData #GraphDatabase

We all want to know “Where does our meat come from?” or “Is this a reliable information or fake news?”. If we ask this kind of questions…

Even with all the buzz around the technology and the snazzy visualisations, graph databases are still a novel concept for many organisations. My recent experience of working with company register relationship data and evaluating graph databases from various vendors led to some interesting insights i

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org - Accenture/AmpliGraph

A comprehensive collection of recent papers on graph deep learning - DeepGraphLearning/LiteratureDL4Graph

Graph+Semantics: Import/Export RDF from Neo4j. SHACL Validation, Model mapping and more.... If you like it, please ★ ⇧ - neo4j-labs/neosemantics

VLog, a new rule based reasoner on #KnowledgeGraphs, with #opensource implementation on #Github #iswc_conf #research #sfotwareengineering h/t

Material for VKG2019 tutorial at ESWC2019. Contribute to oeg-upm/vkg-tutorial-eswc2019 development by creating an account on GitHub.

Cypher for Gremlin adds Cypher support to any Gremlin graph database. - opencypher/cypher-for-gremlin