natanael.arndt.xyz: Decentralized Collaborative Knowledge Management using Git (Extended Abstract)
Collaboration of people and machines is a major aspect of the World Wide Web and as well of the Semantic Web. As a result of the collaboration process, structural and content interferences as wel…
Nelson Piedra retweeted: Ontologies and #Semantic #Annotation. Part 1: What is an #Ontology? bit.ly/2EXtitY —————— #BigData #MachineLearning #AI #DataScience #SmartData #DataLabeling #KnowledgeGraphs #LinkedData #RDF #abdsc —————— ➕See my webinar on this
Ontologies and #Semantic #Annotation. Part 1: What is an #Ontology? https://t.co/Crvkko76SD——————#BigData #MachineLearning #AI #DataScience #SmartData #DataLabeling #KnowledgeGraphs #LinkedData #RDF #abdsc ——————➕See my webinar on this topic: https://t.co/zoSuUBQGMY pic.twitter.com/vn2XCVwAMW— Kirk Borne (@KirkDBorne) January 22, 2020
Neo4j Bloom 1.1: Simple, Powerful & Team Ready [Release]
Discover what's new in the 1.1 release of the Neo4j Bloom graph data visualization tool, including internet browser capabilities and new role-based security.
Neo4j Brings Graph Database and Data Science Together
Enterprises that want to use powerful graph algorithms to discover relationships hidden in their data now have an easier path to get there thanks to the new data science library unveiled today by graph database maker Neo4j.
Neo4j CEO talks growing enterprise graph adoption and why partnering with Google makes sense
(Image sourced via Neo4j’s Twitter)I last met Emil Eifrem, the highly energetic and persuasive founder and leader of graph database and software tools firm Neo4j for diginomica back in May 2017. As he was quick to point out in our latest meeting, a lot’s changed for his company and the market he’s tried to so hard to dominate.
Neo4j Graph Database 3.5: Everything You Need to Know [GA Release]
Discover what's new in the 3.5 release of the Neo4j graph database, including a Go language driver, full-text search and indexing, TLS encryption and more.
Two years ago, Neo4j Bloom™ was announced to the world. Today, I’m excited to announce that we’re bringing graph visualization and exploration to everyone using Neo4j – on any platform.
Neo4j retweeted: The Supreme Court of the United States as a graph database, with Justices as brown nodes, Presidents as green nodes, and appointment, promotion, succession, and the 17 historical periods/Courts associated with each Chief Justice shown thr
The Supreme Court of the United States as a graph database, with Justices as brown nodes, Presidents as green nodes, and appointment, promotion, succession, and the 17 historical periods/Courts associated with each Chief Justice shown through relationships. @mad_cat @tcjericho pic.twitter.com/FdDXHo82H0— 🌍 Јаков Минг Дановић 🌏 (@chenx064) March 4, 2020
Neo4j Startup Program Expands Availability and Benefits
/PRNewswire/ -- Neo4j, the leader in graph databases, announced today that it has expanded the availability of its free Startup Program. Neo4j graph technology...
Neo4j's Graphs4Good Receives Honorable Mention in Fast Company's 2019 World Changing Ideas
/PRNewswire/ -- Neo4j, the leader in graph databases, announced today that its program, Graphs4Good: Building a Better World with Connected Data, received an...
Neptune Streams feature is now available outside of lab mode
log data) as they happen for notifying processes or creating a new copy of the graph in a different region or service such as the Amazon Elasticsearch Service, Amazon ElastiCache, or Amazon Simple Storage Service (S3). Neptune Streams is now available in production from engine release 1.0.2.2.R2. Neptune Streams can be enabled or disabled using the cluster parameter neptune_streams. Once enabled, you can access Neptune Streams using the HTTP GET requests to REST APIs /sparql/streams or /gremlin/streams. The response will be a JSON feed of the operations and the changes to the graph. The lab mode setting “streams” in the database cluster parameter neptune_lab_mode will be removed after the current release. When Neptune Streams are enabled, you incur I/O and storage charges associat
Never mind the logix: taming the semantic anarchy of mappings in ontologies | Monkeying around with OWL
Mappings between ontologies, or between an ontology and an ontology-like resource, are a necessary fact of life when working with ontologies. For example, GO provides mappings to external resources…
New Approaches for Structured Data:Evolution of Question Aswering
Google has moved from Search to Knowledge, and Focusing on Answering questions with knowledge graph entity information provides has led to answering queries w…
Next generation machine learning powered by graph analytics
meters, human capital is almost always the largest single component. To this end, if you want to use smart building technologies to save costs or increase margins, the main use cas
Nicolas Torzec on Twitter: "Pretty standard (knowledge graph) mining of the Grammy artists and their connections. It's nice to see News being mined to discover and rank connections but confusing co-occurrences with factual relationships doesn't look great
Pretty standard (knowledge graph) mining of the Grammy artists and their connections. It's nice to see News being mined to discover and rank connections but confusing co-occurrences with factual relationships doesn't look great.Exhibit: https://t.co/Wkv1ckt7ykvia @aaranged— Nicolas Torzec (@nicolastorzec) February 21, 2019
Nicolas Torzec on Twitter: "Q: which product taxonomies are used in the Shopping / Ad industries? Google's Product Taxonomy is a de facto standard but it lacks freshness, coverage and/or finesse in some areas. I'm also looking at product taxonomies from A
“Q: which product taxonomies are used in the Shopping / Ad industries? Google's Product Taxonomy is a de facto standard but it lacks freshness, coverage and/or finesse in some areas. I'm also looking at product taxonomies from Amazon, Ebay, Walmart, Target, Groupon. What else?”
Nicolas Torzec on Twitter: "The Underlay: MIT project by Danny Hillis (Thinking Machines, Applied Minds, Metaweb/Freebase, etc.) et al., to create a global, public, distributed, machine-readable, knowledge graph that natively focuses on claims and provena
The Underlay: MIT project by Danny Hillis (Thinking Machines, Applied Minds, Metaweb/Freebase, etc.) et al., to create a global, public, distributed, machine-readable, knowledge graph that natively focuses on claims and provenance rather than simple facts. https://t.co/CB8arNKIbg— Nicolas Torzec (@nicolastorzec) December 4, 2018
Node2Vec — Graph Embedding Method - Towards Data Science
Graphs are common #data structures to represent #connecteddata. To use graphs with #deeplearning, we use graph embeddings, a low dimension representations which helps generalize input data. Node2Vec aims to preserve network neighborhoods #datascience #AI
Not Science Fiction - Kurt Cagle's View on Semantic Technologies | SEMANTiCS 2020 US
Kurt Cagle is one of the advisors behind the SEMANTICS 2020 Conference. He is a writer, data scientist and futurist focused on the intersection of computer technologies and society. He is also the founder of Semantical, LLC, a smart data company. In this interview, Kurt shares with us some of his expertise and his vision for the new paths being opened by Semantic Technologies.
suited tool to present data where connections and links are important for us to understand it. Like molecules structure that presents a collection of basic atoms which are linked to other, forming complex structure where each atom’s connection in this collection means something’s in terms of the usage or the characteris