GraphNews

@AllianzBenelux - "we’ve made €2m profit using graph technology"Read @diginomica's full story here: https://t.co/BByFtdRRyq#Neo4j #GraphDatabases #FraudDetection #FinTech— Neo4j (@neo4j) September 25, 2020

“My post on Mount Rainier’s Laplacian (https://t.co/ONdkZJdayX) is a 101 intro to aspects of spectral graph theory. This great talk by @mmbronstein shows how this theory also forms the basis of deep learning on graph-like structures. Read at least 5 papers today because of it. https://t.co/eMsV9...

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

Another exciting application for #graphml With @frederickmonti back in 2018 we have had our excursion into HEP working on neutrino detection with @uw_icecube https://t.co/roiByGczpi— Michael Bronstein (@mmbronstein) September 25, 2020

The discussion on personal #knowledgegraphs is gaining traction. @kurt_cagle had it listed among other most common use cases for knowledge graph application: https://t.co/jLpqZOWJjrhttps://t.co/xxjnlAtti2— Ontotext (@ontotext) 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

"Therefore, the job of data scientists is to decode the data and to find the knowledge encoded in the data—i.e., to find the model in the data, because the data is the model." - @KirkDBorne, @BoozAllen https://t.co/sZJzBkiA1p pic.twitter.com/NpKaDLLUuL— Kirk Borne (@KirkDBorne) September 28, 2020

😉Happy to share our work on multi-hop (open-domain) QA (https://t.co/7BhmCqX64m). TL;DR: you don't need the Wikipedia hyperlinks to achieve SoTA performance on HotpotQA(@qi2peng2 )! A shared RoBERTa encoder (for both Q and docs) is all you need to retrieve SP passages! 1/3 pic.twitter.com/B9JO85Vd1l— Wenhan Xiong (@xwhan_) September 29, 2020

Beyond improving institutional memory, #knowledgegraphs open an organization's data to the growing sophistication of #artificialintelligence. https://t.co/e5WyplfL8i #semantictechnology #linkeddata #knowledgemanagement— Ontotext (@ontotext) September 30, 2020

Interesting paper on which parts of SPARQL query language are easier or more difficult to understand: https://t.co/TgWNXFrCfv— Learning SPARQL (@LearningSPARQL) September 29, 2020

⭕ Insightful Reading: "Semantic #KnowledgeGraphs Soar To The Fore Of #AI" v/@AITimeJournal #BigData #Analytics #DataScience #ML #IoT #IIoT #Python #RStats #TensorFlow #javascript #reactjs #CloudComputing #Linux #programming #coding #Industry40https://t.co/1GQw3IgRUa pic.twitter.com/aCnCY0NCJn— Bomoi Abdulmajid (@Bomoimajid) September 24, 2020

Everything you always wanted to know but never dared to ask about #knowledgeGraphs:On Oct. 27, 2020, our new free online course "Knowledge Graphs" with @lysander07 and @em_alam will start on the @openHPI platform. Register now at https://t.co/UA9XxTOO3O pic.twitter.com/V6YGkV5Pu4— Harald Sack (@lysander07) September 12, 2020

In this blog post, we explore how the performance of Memgraph as evolved across version from v0.15.2 to v1.1.0 and discuss how we were able to reduce memory usage by as much as 50% and improve throughput towards near-linear scalability.https://t.co/R8XTh520CK— Memgraph (@memgraphdb) October 1, 2020

Lots of very good material here. Covers a lot of ground including Amazon Neptune, performance tuning, data modeling, common use cases and also some @apachetinkerpop Gremlin and @w3c RDF tutorials. https://t.co/3gdcKcNHiT— Kelvin Lawrence (@gfxman) October 1, 2020

Ever had some weird dataset you wanted, like "a list of every US senator ever and their gender?" and thought "ugh, that's gonna be a pain to assemble?"Or "Wikipedia has info on X, but it's gonna be hard to get out?"Well, Have you heard of Wikidata?https://t.co/1L6pkFh43h pic.twitter.com/8KiZyKKlSX— Erin ✨💽 (@erincandescent) October 1, 2020

https://t.co/kSTvjW2oBv Such a thoughtful article on #knowledgegraphs! @TDataScience pic.twitter.com/BphubNoYwv— James Le (@le_james94) October 1, 2020

This is just super satisfying. A @GavinMGleason query to combine conflict data from @dbpedia and @SeshatDatabank I love:1. the explosion2. dragging empires around followed by their battles pic.twitter.com/4oxAT8ynAF— TerminusDB (@TerminusDB) October 1, 2020

This current issue of https://t.co/iSEn2yvLfR covers #datagovernance #dataestate #data's #gendergap #datacatalog #dataestate #knowledgegraphs #DMP ... more. New content from @RSeiner @MandySeiner @AJAlgmin Polikoff of @TopQuadrant Beechum and @HBKI71. https://t.co/EEuVW3g7SG pic.twitter.com/sIL7KvLiJp— TDAN (@TDAN_com) October 1, 2020

In case you missed it, the recording of last week's #Lotico session on JSON-LD is now available. https://t.co/Pzlyjh2S89. #jsonld cc/@neumarcx— Gregg Kellogg (@Gkellogg) October 1, 2020

We’re proud to announce that Stardog is joining the Enterprise Knowledge Graph Foundation as a founding vendor member. Read on if you want to learn who, what, and why.

While five new #AI solutions enter the Gartner Hype Cycle for AI, 2020 what trends are dominating this year’s #AI landscape? Read Gartner analyst Svetlana Sicular’s views here. #GartnerSYM #CIO #ML #Chatbot

Most of the world’s knowledge is encoded in natural language (e.g., news articles, books, emails, academic papers). It is estimated that 80 percent of business-relevant information originates in un…

Introduction to timbr and the Covid-19 SQL knowledge graph

Diving into the bowels of a global organization