GraphNews

3.4.0 Highlights - Adding an index to collection values is now a lot easier with index() https://t.co/nn6klvcU5X #graphdb pic.twitter.com/BWVOcc957r— TinkerPop (@apachetinkerpop) January 10, 2019

3.4.0 Highlights - GraphBinary is the new network serialization format that has shown to be significantly faster than the existing options. Expect more developments to come as the 3.4.x line of code develops - https://t.co/GkTEMmmTBJ #graphdb pic.twitter.com/WTMyI8nv6l— TinkerPop (@apachetinkerpop) January 11, 2019

3.4.0 Highlights - The "g" variable,(i.e. the TraversalSource) is the gateway to writing Gremlin. TinkerPop has offered a number of ways to construct it but now those approaches are unified by the static traversal() method https://t.co/EeesiRCdQv #graphdb pic.twitter.com/FORIvmu6F3— TinkerPop (@apachetinkerpop) January 9, 2019

“3.4.0 Highlights - The Gremlin Recipes have been expanded with a new Anti-Patterns section that describes common pitfalls around Gremlin readability, maintainability and performance. https://t.co/NwUNY7zFqY #graphdb”

3.4.0 Highlights - Use #sparql with any TinkerPop-enabled graph system. This feature should be as interesting to graph providers as it is to users because implementing TinkerPop means getting other query languages besides Gremlin for free https://t.co/cBxjH8BCsW #graphdb #rdf pic.twitter.com/dQsXqCJtL2— TinkerPop (@apachetinkerpop) January 9, 2019

Apache TinkerPop 3.2.11 Released. Nine Inch Gremlins https://t.co/niaJ7oB1wK #graphdb #nosql pic.twitter.com/B8NfL8peWT— TinkerPop (@apachetinkerpop) January 9, 2019

Apache TinkerPop 3.3.5 Released. Gremlin Symphony #40 in G Minor https://t.co/lgWIBL4Q23 #graphdb #nosql pic.twitter.com/8UBWfI7aCt— TinkerPop (@apachetinkerpop) January 9, 2019

Apache TinkerPop 3.4.0 Released. Avant-Gremlin Construction #3 for Theremin and Flowers https://t.co/b6wgT8GnuE #graphdb #nosql pic.twitter.com/FnNxhQULfD— TinkerPop (@apachetinkerpop) January 9, 2019

In this post, we go into detail on how we optimized our data pipeline to be ultra efficient to both load historical bitcoin chain data and keep up to date with new blocks as they arrive. Hope you find it useful! 🤓 pic.twitter.com/fuaWXq9gPn— TokenAnalyst (@thetokenanalyst) February 22, 2019

ELMo’s LM was bi-directional, but the openAI transformer only trains a forward LM. A transformer-based model whose LM looks both forward & backwards?-> transformer encoders :: BERT https://t.co/j20F9RFoD5READ:https://t.co/8OsE3c7Vxh#LM_M = Language Model, masked #NLP— Tom (@data_topology) December 14, 2018

If you're using #ApacheSpark to load data into #Neo4j you might be interested in our latest contribution to https://t.co/MzCRWUdu8h.Thanks to @mesirii, we added more functionality to Neo4jDataFrame, improving relationship creation and adding node creation functionality 💪— Tomer Levi (@Tomer_Levi) February 12, 2019

Ontotext's review of the top 5 automation and semantic technology trends to look for in 2019.

SourceThe year 2020 has just started but we can already see the trends of Graph Machine Learning (GML) in the latest research papers. Below is my view on what will be important in 2020 for GML and the discussion of these papers.The goal of this article is not on introducing the basic concepts of GML such as graph neural networks (GNNs), but on…

Read this second blog in a series dedicated towards setting a standard for AI, and why graph technology weaves connections to create much-needed context.

Read the first installment of this four-part series on how graphs provide the context artificial intellingence needs to remain reliable and trustworthy.

Learn what Neo4j CEO Emil Eifrem believes is the most critical component of both technical and ethical standards for AI – and how we might make it happen.

The opportunity is here now to embark on a journey to take back control of your #data. #Enterprises can have one or many #knowledgegraphs for different purposes, domains, #apps. Knowledge becomes encoded, readily usable for humans & machines h/t @aaranged

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The global food supply chain industry is turning to blockchain to ensure global food safety by tracking food farm to table.

By: Pablo Díaz

In the midst of a global pandemic, big data technologies like graph databases are demonstrating a remarkable capability to model complex interactions

Transformer Commonsense Models for Knowledge Graph Construction [PDF] @abosselut et al. h/t @bill_slawski https://t.co/P5BUvjNApA pic.twitter.com/v4Gx9ExtPV— Aaron Bradley (@aaranged) June 28, 2019

Your one-stop introduction to the world of graph tech.

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About two weeks ago, I had the pleasure of attending the 1st Conference on Automated Knowledge Base Construction held in Amherst, Massachusetts. This conference follows up on a number of successful…

From June 2 – 6, I had the pleasure of attending the Extended Semantic Web Conference 2019 held in Portorož, Solvenia. After ESWC, I had another semantic web visit with Axel Polleres, Sabrina…