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Machines learn language better by using a deep understanding of words – TechCrunch
Machines learn language better by using a deep understanding of words – TechCrunch
Computer systems are getting quite good at understanding what people say, but they also have some major weak spots. Among them is the fact that they have trouble with words that have multiple or complex meanings. A new system called ELMo adds this critical context to words, producing better understanding across the board.
·techcrunch.com·
Machines learn language better by using a deep understanding of words – TechCrunch
Magic Quadrant for Metadata Management Solutions
Magic Quadrant for Metadata Management Solutions
.@Gartner Magic Quadrant for Metadata Management Solutions is out, and includes 2 vendors whose solutions rely on #knowledgegraphs #semantics #ontology #graphdatabase Congrats @datadotworld @semwebcompany https://www.gartner.com/en/documents/3970385
·gartner.com·
Magic Quadrant for Metadata Management Solutions
Making Wikidata visible | Bodleian Digital Library
Making Wikidata visible | Bodleian Digital Library
→ Cet article en Français I’ve been experimenting with a way to show how Wikidata represents knowledge; specifically how it makes pathways out of relationships between things. In a previous p…
·blogs.bodleian.ox.ac.uk·
Making Wikidata visible | Bodleian Digital Library
Managing Delivery Networks: A Use Case For Graph Databases - DEV Community 👩‍💻👨‍💻
Managing Delivery Networks: A Use Case For Graph Databases - DEV Community 👩‍💻👨‍💻
An analysis of the unique problem @TAKEALOT faced in facilitating reliable deliveries to customers and how they use a #graphdatabase to deliver a performant and scalable solution, by @filipe_ppt #retail #business #innovation #data https://dev.to/fppt/managing-delivery-networks-a-use-case-for-graph-databases-2jb0
·dev.to·
Managing Delivery Networks: A Use Case For Graph Databases - DEV Community 👩‍💻👨‍💻
Marc RobinsonRechavi on Twitter: "New preprint by Ana Claudia Sima & Tarcisio Mendes de Farias et al, with @cdessimoz and many who aren't on Twitter: Enabling Semantic Queries Across Federated Bioinformatics Databases Federating @OMABrowser @uniprot @Bgee
Marc RobinsonRechavi on Twitter: "New preprint by Ana Claudia Sima & Tarcisio Mendes de Farias et al, with @cdessimoz and many who aren't on Twitter: Enabling Semantic Queries Across Federated Bioinformatics Databases Federating @OMABrowser @uniprot @Bgee
New preprint by Ana Claudia Sima & Tarcisio Mendes de Farias et al, with @cdessimoz and many who aren't on Twitter: Enabling Semantic Queries Across Federated Bioinformatics DatabasesFederating @OMABrowser @uniprot @Bgeedb #SPARQL #RDFhttps://t.co/zHHgrSMH8K— Marc RobinsonRechavi #WearADamnMask (@marc_rr) July 1, 2019
·twitter.com·
Marc RobinsonRechavi on Twitter: "New preprint by Ana Claudia Sima & Tarcisio Mendes de Farias et al, with @cdessimoz and many who aren't on Twitter: Enabling Semantic Queries Across Federated Bioinformatics Databases Federating @OMABrowser @uniprot @Bgee
Marko A. Rodriguez on Twitter
Marko A. Rodriguez on Twitter
My thoughts on the future of @apachetinkerpop.I believe:Apache TinkerPopA Graph Computing Frameworks==should become==>Apache TinkerPopA Distributed Computing Virtual Machine and Languagehttps://t.co/Z5BKnewpS0 #graphdb #nosql pic.twitter.com/yX2wvoRaYQ— Marko A. Rodriguez (@twarko) February 26, 2019
·twitter.com·
Marko A. Rodriguez on Twitter
Martynas Jusevicius on Twitter: "Am I the only one who thinks there's nothing really wrong with the #RDF stack? To me it's such a powerful technology that 20 years in we're still exploring what it is capable of. To do that, we need to throw out the old so
Martynas Jusevicius on Twitter: "Am I the only one who thinks there's nothing really wrong with the #RDF stack? To me it's such a powerful technology that 20 years in we're still exploring what it is capable of. To do that, we need to throw out the old so
Am I the only one who thinks there's nothing really wrong with the #RDF stack?To me it's such a powerful technology that 20 years in we're still exploring what it is capable of. To do that, we need to throw out the old software design paradigms and think graph- and Web-native.— Martynas Jusevicius (@namedgraph) November 27, 2018
·twitter.com·
Martynas Jusevicius on Twitter: "Am I the only one who thinks there's nothing really wrong with the #RDF stack? To me it's such a powerful technology that 20 years in we're still exploring what it is capable of. To do that, we need to throw out the old so
Massively parallel implementation of #Graph2Vec = scalable graph representation #algorithm learns vectors that describe whole graphs in an embedding space:github.com/benedekrozembe… by @benrozemberczki#BigData #DataScience #AI #MachineLearning #LinkedData
Massively parallel implementation of #Graph2Vec = scalable graph representation #algorithm learns vectors that describe whole graphs in an embedding space:github.com/benedekrozembe… by @benrozemberczki#BigData #DataScience #AI #MachineLearning #LinkedData
Massively parallel implementation of #Graph2Vec = scalable graph representation #algorithm learns vectors that describe whole graphs in an embedding space:https://t.co/nR0Iv2QG4u by @benrozemberczki#BigData #DataScience #AI #MachineLearning #LinkedData #GraphDB #GraphAnalytics pic.twitter.com/7INPwfeDPw— Kirk Borne (@KirkDBorne) August 25, 2019
·twitter.com·
Massively parallel implementation of #Graph2Vec = scalable graph representation #algorithm learns vectors that describe whole graphs in an embedding space:github.com/benedekrozembe… by @benrozemberczki#BigData #DataScience #AI #MachineLearning #LinkedData
Math Riddle From the 1980’s Finally Solved – Could Be Used to Improve Phones and Computers
Math Riddle From the 1980’s Finally Solved – Could Be Used to Improve Phones and Computers
Researchers thought that they were five years away from solving a math riddle from the 1980's. In reality, and without knowing, they had nearly cracked the problem already. Researchers from the University of Copenhagen and the Technical University of Denmark (DTU) thought that they were five year
·scitechdaily.com·
Math Riddle From the 1980’s Finally Solved – Could Be Used to Improve Phones and Computers
Meaning-First Data Modeling, A Radical Return to Simplicity | Semantic Arts
Meaning-First Data Modeling, A Radical Return to Simplicity | Semantic Arts
Meaning-First data modeling for #semantic #knowledgegraphs: a replacement to Structure-First modeling. The relational model was a great start for #datamanagement, but it is time to embrace a radical return to simplicity: Meaning-First data modeling #data
·semanticarts.com·
Meaning-First Data Modeling, A Radical Return to Simplicity | Semantic Arts
Memorizing vs. Understanding (read: Data vs. Knowledge)
Memorizing vs. Understanding (read: Data vs. Knowledge)
up the value of e anytime I need it (figure 1);Figure 1. A data dictionary with key and value of arithmetic expressions.(ii) if I do not have that option then the only other alternative to get the value of e is to actually compute the arithmetic expression and get the corresponding value. The first method, let’s call it the data/memorization method, which does not require me to know how to compute e while the second does. That is, in using the second method I (or the computer!) must know the procedures of addition and multiplication, shown in figure 2 below (where Succ is the ‘successor’ function that returns the next natural number).Figure 2. Theoretical definition of the procedures/functions of addition and multip
·medium.com·
Memorizing vs. Understanding (read: Data vs. Knowledge)
Metadata Recycling into… by Thomas Frisendal [PDF/iPad/Kindle]
Metadata Recycling into… by Thomas Frisendal [PDF/iPad/Kindle]
Recycle, Reuse and Reduce also for data models! Why waste time remodeling the same data, just because you go to graph? Learn how to auto-generate graph data models (for Neo4j) from legacy data models in UML, XML, ERD, concept maps and other formats. Missing something on the list? Let the author know! New: FileMaker db's as Graph Data Models!
·leanpub.com·
Metadata Recycling into… by Thomas Frisendal [PDF/iPad/Kindle]
Michael Pollmeier on Twitter
Michael Pollmeier on Twitter
This is so cool, this is the first time for me to ship a #Scala REPL based product. The @apachetinkerpop based DSL allows to query your own codebase for security vulnerabilitries, data leaks etc. https://t.co/1xSOwCnhI3— Michael Pollmeier (@pollmeier) December 11, 2018
·twitter.com·
Michael Pollmeier on Twitter
Microsoft to introduce a free tier of its Cosmos DB NoSQL database
Microsoft to introduce a free tier of its Cosmos DB NoSQL database
at Build 2017. Azure Cosmos DB was designed t be a superset of Microsoft's existing NoSQL Document DB database. Its codename was "Project Florence," and Microsoft execs consider it a "born in the cloud/cloud native" database that's designed to be scalable and usable by customers of any size.Microsoft currently charges by provisioned throughput and consumed storage by the hour for Azure Cosmos DB. Before the introduction of the free tier, M
·zdnet.com·
Microsoft to introduce a free tier of its Cosmos DB NoSQL database
Mind the Semantic Gap
Mind the Semantic Gap
How "talking semantics" can help you perform better #DataScience. @palexop #StrataData talk in New York slides now available #dataModeling #semantics
·slideshare.net·
Mind the Semantic Gap
mm-adt
mm-adt
A blueprint for the next @apachetinkerpop and an analysis on #opensource. @twarko @_mmadt #presentation from @DataDayTexas #GraphDB #data #tech #cloud #insight #softwareengineering #softwaredevelopment #AWS
·slideshare.net·
mm-adt