GraphNews

Over the past few years, growth in the uptake of RDF has picked up steadily. In some domains, such as asset management and systems engineering, this growth is quite significant and driven by national and European standards.

Do Transformers Really Perform Bad for Graph Representation? Ying et al.: https://lnkd.in/dNaPiEf #Transformers #GraphRepresentation #DeepLearning...

Knowledge graphs have been increasingly seen as a way to understand relationships among data. They are used for biological networks, drug information - and chemical reactions.

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"Design Space for Graph Neural Networks" by Jure Leskovec, Jiaxuan You, and Rex Ying "GNN designs are often specialized to a single task, yet few efforts...

Visualizing graphs is hard. Thankfully, a ton of tools have been developed that make graph visualization a cakewalk.

Our latest benchmark report, Trillion Edge Knowledge Graph, is the first demonstration of a massive knowledge graph that consists of materialized data and Virtual Graphs spanning hybrid multicloud data sources. We prove it is possible to have a 1 trillion-edge knowledge graph and deliver sub-second query times while achieving a 98% cost savings.

A visual guide to graph neural networks and over-smoothing issue

Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. It provides both full implementations of state-of-the-art models for data scientists... 26 comments on LinkedIn

Bitnine Promoting a First IPO in the Graph Database Industry This Year https://t.co/Lh9zi7g0ZJ pic.twitter.com/9JJYcUwTQK— Latest News from Business Wire (@NewsFromBW) March 2, 2021

new life sciences SPARQL endpoint. License unclear, and contains (with permisison) some proprietary data (MeSH): https://t.co/HuvlSNhRo3 https://t.co/gSFH7o7Oxo— Egon Willighⓐgen (@egonwillighagen) February 25, 2021

Google introduces the #OpenSource Insights Project Exploratory #visualization provides an interactive view of #OSS projects dependencies A full dependency graph is built/published, incorporating metadata, so you can see how it may affect your #software

Check out the new features in the Neo4j graph data science library v1.6, including improved graph embeddings and better supervised ML pipelines.

In this contributed article, editorial consultant Jelani Harper discusses The how increasing reliance on knowledge graphs parallels that of Artificial [...]

A collection of important graph embedding, classification and representation learning papers with implementations. - benedekrozemberczki/awesome-graph-classification

Microsoft's annual developer event, Build, introduces no revolutionary changes on the data and analytics front, but there's a long manifest of new evolutionary features and service tiers.

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[vc_row type=”in_container” full_screen_row_position=”middle” scene_position=”center” text_color=”dark” text_align=”left” overlay_strength=”0.3″ shape_divider_position=”bottom”][vc_column column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” width=”1/1″ tablet_text_alignment=”default” phone_text_alignment=”default” column_border_width=”none” column_border_style=”solid”][vc_column_text]What Is Ethical AI? Ethical, or responsible, artificial intelligence (AI), “is the...

A community reveals the features and connections of its members that are different from those in other communities in a network. Detecting communities is of great significance in network analysis....

I have been working on Awesome Graph Classification for years. It is a collection of ML techniques that solve graph classification problems: kernels, statistical...

This series summarizes a comprehensive taxonomy for machine learning on graphs and reports details on GraphEDM (Chami et. al), a new framework for unifying different learning approaches. Graphs are…

This blog discusses SHACL capabilities and advantages of modeling in SHACL. It also debunks some myths about SHACL's shortcomings.

This blog discusses why, after being a strong supporter of using OWL, I no longer use it and had completely abandoned it in favor of SHACL.

In the world of asset management, data exchange is a big thing. Modelling the underlying information is a central tenet in Building Information Modelling (BIM).

I plan to add this quote to a slide someday: "“Linked Data” is a broad marketing euphemism for RDF that emphasises some but not all of its strengths, such as the ease of data merging across loosely coupled systems. But it is not a technical term or a W3C standard as such."

@aaranged @JayGray0919 @bobdc @libbymiller @linkedktk @Anastas81377670 https://t.co/ooIuC1elTy can be annoying to consume so more tooling like @Anastas81377670 ‘s work on https://t.co/uUJHzs84vL (integrates opensource parsing + shape validation tools with a friendly API) is needed for developers as well as publishers.

In recent years, knowledge graphs have been widely applied to organize data in a uniform way and enhance many tasks that require knowledge, for example, online shopping which has greatly...

Last year, we announced the general availability of the Azure Digital Twins platform. The associated open modeling language, Digital Twins Definition Language (DTDL), is a blank canvas which can model any entity. It is therefore important to provide common domain-specific ontologies to bootstrap sol...