GraphNews

#KnowledgeGraph #GraphAnalytics
"What are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web."
"What are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web."
"What are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web."(Haller et al, 2019)https://t.co/wE8nEH0ugn pic.twitter.com/2q22ow6jB4— WikiResearch (@WikiResearch) October 10, 2019
·twitter.com·
"What are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web."
(20) Aaron Bradley on Twitter: "#schema.org 5.0 released. No additions to core, but vocabulary for the classification of health topics for more real estate properties in development. https://t.co/BEQsWeDQqo https://t.co/o7JKCoLSg0" / Twitter
(20) Aaron Bradley on Twitter: "#schema.org 5.0 released. No additions to core, but vocabulary for the classification of health topics for more real estate properties in development. https://t.co/BEQsWeDQqo https://t.co/o7JKCoLSg0" / Twitter
#schema.org 5.0 is out. No additions to core, but vocabulary for classification of #healthcare topics for more real estate properties in development. New releases on 1st of month, changes in "Pending" section #SEO #semantics #Google h/t @danbri @aaranged
·twitter.com·
(20) Aaron Bradley on Twitter: "#schema.org 5.0 released. No additions to core, but vocabulary for the classification of health topics for more real estate properties in development. https://t.co/BEQsWeDQqo https://t.co/o7JKCoLSg0" / Twitter
20 Data Trends for 2020
20 Data Trends for 2020
#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
·towardsdatascience.com·
20 Data Trends for 2020
3 ways that #DataVisualization will advance and impact users (including Knowledge Graphs): bit.ly/31vf7pw——————#BigData #DataScience #DataViz #VisualAnalytics #AnalyticsStrategy #DataStorytelling #KnowledgeGraphs #abdsc
3 ways that #DataVisualization will advance and impact users (including Knowledge Graphs): bit.ly/31vf7pw——————#BigData #DataScience #DataViz #VisualAnalytics #AnalyticsStrategy #DataStorytelling #KnowledgeGraphs #abdsc
3 ways that #DataVisualization will advance and impact users (including Knowledge Graphs): https://t.co/3XELwiVDDJ——————#BigData #DataScience #DataViz #VisualAnalytics #AnalyticsStrategy #DataStorytelling #KnowledgeGraphs #abdsc pic.twitter.com/N43Wx3APs2— Kirk Borne (@KirkDBorne) August 9, 2019
·twitter.com·
3 ways that #DataVisualization will advance and impact users (including Knowledge Graphs): bit.ly/31vf7pw——————#BigData #DataScience #DataViz #VisualAnalytics #AnalyticsStrategy #DataStorytelling #KnowledgeGraphs #abdsc
Graph Theory and Data Science
Graph Theory and Data Science
Graph Theory and #DataScience: A topic intro with the Bridges of Königsberg. Graph Theory can be used to represent and analyze a wide variety of network information, has numerous modern applications within Data Science #data #tech #software #algorithms
·towardsdatascience.com·
Graph Theory and Data Science
A Dictionary of Graph Terms | LinkedIn
A Dictionary of Graph Terms | LinkedIn
a general list of terms and phrases used frequently in the Semantics and Property Graph space. It is far from comprehensive, but if you've ever read my or other writers' articles, you may have run across terms that were unfamiliar. I'm publishing this here, with the intent of periodically updating it as time and resources permit.
·linkedin.com·
A Dictionary of Graph Terms | LinkedIn
Aaron Bradley on Twitter: "In your opinion which structured data markup syntax is the easiest to use when adding #schema.org information to a web page?"
Aaron Bradley on Twitter: "In your opinion which structured data markup syntax is the easiest to use when adding #schema.org information to a web page?"
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
·twitter.com·
Aaron Bradley on Twitter: "In your opinion which structured data markup syntax is the easiest to use when adding #schema.org information to a web page?"
Andrei Kashcha on Twitter
Andrei Kashcha on Twitter
https://t.co/7T0EOs6yG7 - Made this tiny tool to discover related subreddits.The graph is created based on jaccard similarity between two subreddits. Jaccard similarity is constructed from set of shared users.Source code https://t.co/J9r1jl1JjR pic.twitter.com/4hcg7mI4sg— Andrei Kashcha (@anvaka) January 10, 2019
·twitter.com·
Andrei Kashcha on Twitter
Announcing Neo4j for Graph Data Science
Announcing Neo4j for Graph Data Science
grade features and scale. We appreciate your candid stories and collaboration, and we’ve used this to create a better solution. As such, we’re excited to announce Neo4j for Graph Data Science™, the first data science environment built to harness the predictive power of relationships for enterprise deployments. Neo4j for Graph Data Science is an ecosystem of tools that includes: With Neo4j for Graph Data Science, data scientists are empowered to confide
·neo4j.com·
Announcing Neo4j for Graph Data Science
CS 520: Knowledge Graphs
CS 520: Knowledge Graphs
Knowledge graphs have emerged as a compelling abstraction for organizing world's structured knowledge over the internet, capturing relationships among key entities of interest to enterprises, and a way to integrate information extracted from multiple data sources. Knowledge graphs have also started to play a central role in machine learning and natural language processing as a method to incorporate world knowledge, as a target knowledge representation for extracted knowledge, and for explaining what is being learned. This class is a graduate level research seminar featuring prominent researchers and industry practitioners working on different aspects of knowledge graphs. It will showcase how latest research in AI, database systems and HCI is coming together in integrated intelligent systems centered around knowledge graphs.The seminar will be offered over Zoom as per the planned schedule.The seminar is open to public. Remote participants may join the seminar through Zoom. To be
·web.stanford.edu·
CS 520: Knowledge Graphs
Diego Moussallem retweeted: New from Google Research! REALM: realm.page.link/paper We pretrain an LM that sparsely attends over all of Wikipedia as extra context. We backprop through a latent retrieval step on 13M docs. Yields new SOTA results for open do
Diego Moussallem retweeted: New from Google Research! REALM: realm.page.link/paper We pretrain an LM that sparsely attends over all of Wikipedia as extra context. We backprop through a latent retrieval step on 13M docs. Yields new SOTA results for open do
New from Google Research! REALM: https://t.co/kS2oTyxAAjWe pretrain an LM that sparsely attends over all of Wikipedia as extra context. We backprop through a latent retrieval step on 13M docs. Yields new SOTA results for open domain QA, breaking 40 on NaturalQuestions-Open! pic.twitter.com/DYDFX69Td8— Kelvin Guu (@kelvin_guu) February 11, 2020
·twitter.com·
Diego Moussallem retweeted: New from Google Research! REALM: realm.page.link/paper We pretrain an LM that sparsely attends over all of Wikipedia as extra context. We backprop through a latent retrieval step on 13M docs. Yields new SOTA results for open do
Do Graph Databases Scale? - DZone Big Data
Do Graph Databases Scale? - DZone Big Data
Graph Databases are a great solution for many modern use cases: Fraud Detection, Knowledge Graphs, Asset Management, Recommendation Engines, IoT, Permission Management … you name it.  All such projects benefit from a database technology capable of analyzing highly connected data points and their relations fast – Graph databases are designed for these tasks. But the nature of graph data poses challenges when it comes to *buzzword alert* scalability. So why is this, and are graph databases capable of scaling? Let’s see... In the following, we will define what we mean by scaling, take a closer look at two challenges potentially hindering scaling with graph databases, and discuss solutions currently available. What Is the “Scalability of Graph Databases”? Let’s quickly define what we mean here by scaling, as it is not “just” putting more data on one machine or throwing it on various ones. What you want when working with large or growing datasets is also an acceptabl
·dzone.com·
Do Graph Databases Scale? - DZone Big Data