You’ve probably seen web editors based on the idea of blocks. I’m typing this in WordPress, which has a little + button that brings up a long list of potential blocks that you can inser…
Caroline Goulard on LinkedIn: #dataviz #GrandParis #opendata | 36 comments
🧪 From an internal lab project to a project for the future of Dataveyes 🚀 We are very proud to introduce Modality, our analysis and visualisation tool... 36 comments on LinkedIn
How Solid Pods May End Up Becoming the Building Blocks of the Metaverse - DataScienceCentral.com
Tim Berners-Lee has an interesting habit of coming up with ideas that seem hard to explain at the outset, remain all hard to understand even as they become more implemented and refined, can go for years with only a few die-hard fans becoming convinced that what he is doing is the best thing since sliced… Read More »How Solid Pods May End Up Becoming the Building Blocks of the Metaverse
TigerGraph: Graph DBs to Become a ‘Must-Have’ in 2022
Graph databases will no longer be a luxury but will become a "must-have" for enterprise IT organizations in 2022, according to graph database provider TigerGraph. According to Gartner's research, by 2025, graph technologies will be used in 80% of new data and analytics systems, up from 10% in 2021, facilitating rapid decision-making across the enterprise.…
Dagstuhl 2022: Graph Databases and Network Visualization | Stardog
Pavel Klinov, Stardog VP of Research and Development, is back from the Dagstuhl Seminar on Graph Databases and Network Visualization, held at the Leibniz Center for Informatics in Germany from January 16 – 21, 2022. We asked him about his experience.
Metaphors we ontologize by - Casey Hart, Ph.D., Olive
Rather than using mathematical graphs and relational databases, Dr. Hart explains the use and development of ontologies using everyday metaphorical scenarios.
Advanced data science, machine learning and the power of knowledge graphs: What can we expect from this combination?
Knowledge graphs are a powerful way to assist data scientists to crack hard data problems, but they aren’t as widely known as they could be. Graph database expert Maya Natarajan explains why that’s changing.
Utilising Graph Machine Learning within Drug Discovery and Development
Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships...
DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation? - DataScienceCentral.com
Can Machine Learning Do Symbolic Manipulation? I spent some time over the holidays engaged in a fascinating online conversation. The gist of it was a variation of an argument that has been going on in the realm of artificial intelligence from the time of Minsky and Seymour Papert: Whether it is possible for neural networks to… Read More »DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation?
How and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks. By Leo Meyerovich and Ben Lorica. [A version of this post originally appeared on the Graphistry blog.] In this post, we highlight the current state of Graph Intelligence, a new technology category around new tools and techniques forContinue reading "What is Graph Intelligence?"
Claudio Stamile on LinkedIn: #machinelearning #ai #datascience
AutoML on graphs is a thing. In the paper Automated Machine Learning on Graphs: A Survey (https://lnkd.in/djs25FfM), the authors present a comprehensive...
Hannes Stärk on LinkedIn: Neural Bellman-Ford Networks | Zhaocheng Zhu
New Video! Zhaocheng Zhu explains his paper NeurIPS'21 paper "Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction...
Where Semantics and Machine Learning Converge - DataScienceCentral.com
Artificial Intelligence has a long history of oscillating between two somewhat contradictory poles. On one side, exemplified by Noam Chomsky, Marvin Minsky, Seymour Papert, and many others, is the idea that cognitive intelligence was algorithmic in nature – that there were a set of fundamental precepts that formed the foundation of language, and by extension,… Read More »Where Semantics and Machine Learning Converge
Deep Learning with Graph-Structured Representations
Very honored to receive the ELLIS PhD Award for my thesis on Deep Learning with Graph-Structured Representations -- alongside with with @NagraniArsha for her work on multimodal DL (congrats!) https://t.co/FUzNA87okN pic.twitter.com/W2KrbQN7yS— Thomas Kipf (@thomaskipf) December 9, 2021
Understand the ROI of an Enterprise Knowledge Graph Platform | Stardog
Enterprise Knowledge Graph Platform ROI: Providing readers with a framework to evaluate the potential financial impact of deploying Stardog on their own organizations.
Interested in using Wikidata & Wiktionary to extract lexicographical information?@sina_ahm created a simple SPARQL query generator that helps non-experts get familiar w/ #SPARQL & create queries to look up words in @wikidata & #Dbnary:👉 https://t.co/gS6JG8EIFb#NLProc pic.twitter.com/9UOCABh3c9— ELEXIS EU (@elexis_eu) December 1, 2021
Curious about the most used ontologies in the agri-food domain? Our #Ontologies Community of Practice has developed a webpage featuring the most popular ontologies & info on those developed by @CGIAR and partners.Find it here: https://t.co/AMVeSHCpdi pic.twitter.com/LmazTo4V2T— CGIAR Platform for Big Data in Agriculture (@CGIAR_Data) December 9, 2021
"... most Entity Linking approaches use Wikidata in the same way as any other knowledge graph missing the chance to leverage Wikidata-specific characteristics to increase quality" > Survey on English Entity Linking on Wikidata https://t.co/JYHJMfVHsO pic.twitter.com/hRxRp3nhnQ— Aaron Bradley (@aaranged) December 10, 2021
ISEEQ: Information Seeking Question Generation using Dynamic Meta-Information Retrieval and Knowledge Graphs @manasgaur90 et al. https://t.co/Gg6s7J0kwH pic.twitter.com/kNbaji06Vf— Aaron Bradley (@aaranged) December 15, 2021
A Simple Standard for Sharing Ontological Mappings (SSSOM) @NicoMatentzoglu + ~40 others https://t.co/rCAyGakxdY pic.twitter.com/GK0fzPFx6q— Aaron Bradley (@aaranged) December 15, 2021
What if we model a graph as a set of subgraphs instead of a set of interconnected nodes? Hint: expressive power + equivariance! 🧵Joint work by a super team: @beabevi_ * @dereklim_lzh * @balasrini32 @ChenCaiUCSD @gblearning42 @mmbronstein @HaggaiMaronhttps://t.co/6rW4e47RhN pic.twitter.com/Ajl8L5xdDc— Fabrizio Frasca (@ffabffrasca) December 15, 2021
MedGraph: An experimental semantic information retrieval method using knowledge graph embedding for the biomedical citations indexed in PubMed https://t.co/B3tmoVilDt pic.twitter.com/DvEVoU53ec— Aaron Bradley (@aaranged) December 14, 2021