GraphNews

Designing Web APIs for sustainable interactions within decentralized knowledge graph ecosystems ◆ Web services emerged in the late 1990s as a way to access specific pieces of remote functionality, building on the standards-driven stability brought by the universal protocol that HTTP was readily becoming. Interestingly, the Web itself has drastically changed since…

Knowledge graphs are well-suited to organizations with large data sets and where extracting knowledge often proves burdensome.

Implementation of information extraction pipeline that includes coreference resolution, entity linking, and relationship extraction…

Bob Muglia, the former CEO of Snowflake, discusses what’s next for the tooling and technologies powering data analytics and engineering.

Traversing the Tree of Life, using Neo4j

A blog about my work and fun with Neo4j, the world's leading graph database platform.

Hot trends and major advancements

How knowledge graph technologies can help clinical natural language processing

Since the launch of its genesis network in January 2019, the OriginTrail project has yielded a crucial advancement for the foundation of…

The expressive power of Message-Passing Graph Neural Networks is inherently limited due to their equivalence to the Weisfeiler-Lehman graph isomorphism...

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same...

Excited to share a Colab tutorial on graph neural networks with the JAX+Jraph stack, which we use in-house at DeepMind! Developed by Lisa Wang and Nikola... 12 comments on LinkedIn

"The Open Application Group (OAGi) and the Industrial Ontologies Foundry (IOF) have signed an agreement to produce industrial ontologies." [PR] https://t.co/zz511UBuYE— Aaron Bradley (@aaranged) March 3, 2021

Identifying Ingredient Substitutions Using a Knowledge Graph of Food https://t.co/5pZWc9Bt94 pic.twitter.com/PgkMr9idHj— Aaron Bradley (@aaranged) March 3, 2021

Introduction to timbr and the Covid-19 SQL knowledge graph

Excited that our graph Transformer has been accepted as a Contributed Talk to NeurIPS ML and Physical Sciences workshop (TOP 3 out of 151) :D Thanks to...

Why enterprise ontology management matters to the EKG industry

Our work has been published in Nature!!! (G)NNs can successfully guide the intuition of mathematicians & yield top-tier results -- in both representation... 48 comments on LinkedIn

Last week Google added Graph Neural Network support to TensorFlow. This comes in the wake of PyTorch Geometric getting a lot of support from Meta (formerly...

[DevFest Casablanca 2021 Speakers 😎] Anas AIT AOMAR, Engineering Student at Emines school of industrial management. who also payback to the community...

After years of writing a graph data science blog, I've decided to present all my learning in a more guided and structured way. Today I am happy to announce...

Earlier this month I asked here on LinkedIn about interest publishing a short piece on Knowledge Graphs. The response was overwhelmingly positive, so today...

G.V() is an all-in-one Gremlin IDE to write, test and analyze results for your TinkerPop-enabled graph database - in open beta now and looking for feedback: https://t.co/0FLK7kC9K9 #graphdb pic.twitter.com/7U8PeKFsm9— TinkerPop (@apachetinkerpop) November 22, 2021

How to tune the hyperparameters of FastRP to your specific problem

New perspectives on old problems in Graph ML

Beyond listing superficial benefits and implications: Let’s explore what the fundamental difference of the two is.

Learn more about content hubs and how to build them by leveraging deep learning and data in a knowledge graph and using a specific technique called knowledge graph embeddings (or simply KGE).