"The UI allows individuals with no previous knowledge of the Semantic Web to query the DBpedia knowledge base...." > Interface to Query and Visualise Definitions from a Knowledge Base @anelia12430996 & Hélène De Ribaupierre https://t.co/QGSJSEq4Ab pic.twitter.com/EIhZRVikK0— Aaron Bradley (@aaranged) March 15, 2021

NetVec: A Scalable Hypergraph Embedding System https://t.co/CHaT76MA7T pic.twitter.com/ZVChTtb0zH— Aaron Bradley (@aaranged) March 18, 2021

Nice machine learning read of the week: E(n) Equivariant Graph Neural Networks. The paper: https://lnkd.in/dfZ3Gh4 Source code: https://lnkd.in/dNfzQRj...

Knowledge about entities and their interrelations is a crucial factor of success for tasks like question answering or text summarization. Publicly available knowledge graphs like Wikidata or...

Accurate cardinality estimates are a key ingredient to achieve optimal query plans. For RDF engines, specifically under common knowledge graph processing workloads, the lack of schema, correlated...

This paper introduces a new model to learn graph neural networks equivariant to rotations, translations, reflections and permutations called E(n)-Equivariant Graph Neural Networks (EGNNs). In...

Recent years have seen the growing adoption of non-relational data models for representing diverse, incomplete data. Among these, the RDF graph-based data model has seen ever-broadening adoption,...

Basic Introduction to what Graph Analytics is…

We have a new paper showing that #GraphNeuralNetworks are state-of-the-art for representations for #ElectronicHealthRecords data!! EHR data is inherently... 46 comments on LinkedIn

I'm so excited to share this! 🚀✨ My latest research project was to model the interactions between drugs and various biological targets in the body to... 15 comments on LinkedIn

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

Your guide to the KG-related research in NLP, December edition

Link Prediction in #KnowledgeGraphs with an Explainable AI approach that supports newly emerging entitiesPresented this week at #ISWC2020 Joint work w/ @kingsaintrb Code: https://t.co/OzjaefFFoLPaper:https://t.co/4saczQ0slx pic.twitter.com/BnY03YtYTc— Gerard de Melo (@gdm3000) November 4, 2020

Part 1 : Encoding KG Aliases in Attentive Neural Network for Entity Linking (ARJUN)

"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

Learn how DeepWalk treats creating graph embeddings as equivalent to creating word embeddings

“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

Knowledge Graphs at a glance by @giuseppe_futia in @TDataScience https://t.co/q5W3CLUXSj— Teodora Petkova (@TheodoraPetkova) September 28, 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

Use KronoGraph, the time visualization toolkit for JavaScript developers, to build interactive, scalable timeline tools to explore evolving relationships and events.

based diagnosis of disease, and drug repurposing. Integrating data and knowledge is a formidable challenge in biomedical research. Although new scientific findings are being discovered at a rapid pace, a large proportion of that knowledge is either locked in data silos (where integration is hindered by differing nomenclature, data models, and lice

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#Semantic #technology, decision intelligence, knowledge #datascience will be our companions in the next years, so it's recommended to start exploring #graphdatabases, #ontologies, knowledge representation systems #knowledgegraph #AI #2020NewYear #trends

GPU->Rapids->Cugraph->Scalable Graph Analytics

Reasoning over paths in large scale #knowledgegraphs has many applications. @healx #research on approach to automatically build & rank paths between source & target entity pair with learned embeddings using a knowledge base completion model #EmergingTech

world domain. A cursory Google search will result in

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