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Muhammad Saleem on Twitter: ""How Representative is a SPARQL Benchmark? An Analysis of RDF Triplestore Benchmarks" has been accepted as full paper to #www2019 #webconf2019. @DiceResearch @akswgroup @NgongaAxel"
Muhammad Saleem on Twitter: ""How Representative is a SPARQL Benchmark? An Analysis of RDF Triplestore Benchmarks" has been accepted as full paper to #www2019 #webconf2019. @DiceResearch @akswgroup @NgongaAxel"
"How Representative is a SPARQL Benchmark? An Analysis of RDF Triplestore Benchmarks" has been accepted as full paper to #www2019 #webconf2019. @DiceResearch @akswgroup @NgongaAxel— Muhammad Saleem (@saleem_muhamad) January 21, 2019
·twitter.com·
Muhammad Saleem on Twitter: ""How Representative is a SPARQL Benchmark? An Analysis of RDF Triplestore Benchmarks" has been accepted as full paper to #www2019 #webconf2019. @DiceResearch @akswgroup @NgongaAxel"
My list of 7 great 2018 advancements in Enterprise Knowledge Graphs (and 2019 recommendations) | LinkedIn
My list of 7 great 2018 advancements in Enterprise Knowledge Graphs (and 2019 recommendations) | LinkedIn
While the term “Knowledge Graph” is relatively new (Google 2012) the concept of “representing knowledge as a set of relations between entities - forming a “graph” has been around for much longer. 2019 marks, for example, the 20th anniversary of the publication of arguably the first open standard for
·linkedin.com·
My list of 7 great 2018 advancements in Enterprise Knowledge Graphs (and 2019 recommendations) | LinkedIn
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
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
·twitter.com·
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
Neo4j Brings Graph Database and Data Science Together
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.
·datanami.com·
Neo4j Brings Graph Database and Data Science Together
Neo4j CEO talks growing enterprise graph adoption and why partnering with Google makes sense
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.
·diginomica.com·
Neo4j CEO talks growing enterprise graph adoption and why partnering with Google makes sense
Neo4j Is in Bloom Everywhere This Spring
Neo4j Is in Bloom Everywhere This Spring
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.com·
Neo4j Is in Bloom Everywhere This Spring
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
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
·twitter.com·
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
Neptune Streams feature is now available outside of lab mode
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
·aws.amazon.com·
Neptune Streams feature is now available outside of lab mode
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
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
·twitter.com·
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
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
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?”
·twitter.com·
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