Awesome Graph Classification
I have been working on Awesome Graph Classification for years. It is a collection of ML techniques that solve graph classification problems: kernels, statistical...
GraphNews
Graph Representation Learning — The Encoder-Decoder Model (Part 2)
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…
Why I Use SHACL For Defining Ontology Models — TopQuadrant, Inc
This blog discusses SHACL capabilities and advantages of modeling in SHACL. It also debunks some myths about SHACL's shortcomings.
Why I Don't Use OWL Anymore — TopQuadrant, Inc
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.
Real-World BIM: Analysing Different Modelling Options in Published Object Type Libraries | LinkedIn
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).
Bob DuCharme on Twitter: "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."" / Twitter
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."
Dan Brickley on Twitter: "@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." / Twitter
@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.
Billion-scale Pre-trained E-commerce Product Knowledge Graph Model
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...
Energy Grid Ontology for Digital Twins is Now Available
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...
GML In-Depth: three forms of self-supervised learning
"Excelling at chess has long been considered a symbol of more general intelligence. That is an incorrect assumption in my view, as pleasant as it might be." Garry Kasparov
Some lessons learned from building standards around Schema.org – Lost Boy
OpenActive is a community-led initiative in the sport and physical activity sector in England. It’s goal is to help to get people healthier and more active by making its easier for people to …
Strings to things in context — Sharing and learning Phil Barker's work
As part of work to convert plain JSON records to proper RDF in JSON-LD I often want to convert a string value to a URI that identifies a thing (real world concrete thing or a concept). Simple string to URI mapping Given a fragment of a schedule in JSON {"day": "Tuesday"} As well as converting … Continue reading Strings to things in context →
Play detective on Reddit: Discover political disinformation campaigns, secret influencers and more
Play detective on Reddit: Discover political disinformation campaigns, secret influencers and morehttps://t.co/J6kYL6TM2w#api #social #data #socialMedia #database #reddit #politics #etl #analytics #neo4j #graph #analysis #socialNetwork #network #graphDatabase #etl #graphdb pic.twitter.com/KjXAQMJbHI— Luc Michalski (@lucmichalski) May 8, 2021
Bob DuCharme on Twitter
Can anyone tell me about existing projects that pull RDF as JSON-LD (especially https://t.co/Rxky83WuLZ data) from web pages and then do things with it?
Notion data model
Heard of Notion.so? Most people can't quite put their finger on what makes this popular collaborative workspace different than other tools they've used... 13 comments on LinkedIn
What Makes Graph Convolutional Networks Work?
By now, if you’ve been following this series, you may have learned a bit about graph theory, why we care about graph structured data in data science, and what the heck a “Graph Convolutional Network”…
Pinterest’s Use of AI Drives Growth
Using neural networks, the site is able to find images—and ads—that will catch the consumer’s eye.
Keeping Your Sanity with Machine Taxonomization
Taxonomies are crucial for businesses and institutions to handle bigger amounts of data. Manually organizing thousands of concepts into a knowledge tree has so far been the only way to do this. Aside
KELM: Integrating Knowledge Graphs with Language Model Pre-training Corpora
Posted by Siamak Shakeri, Staff Software Engineer and Oshin Agarwal, Research Intern, Google Research Large pre-trained natural language...
Causaly raises $17 million to accelerate biomedical research and discovery of scientific breakthroughs
Causaly, the London-based company that allows researchers and specialists to intuitively map and navigate the intricate landscape of biomedical research, has raised $17 million from investors to grow its team and expand into new markets.
What is GraphQL? An introduction | MuleSoft
GraphQL is a query language for APIs. The APIs that provide a GraphQL interface to query data are called GraphQL APIs. They provide an easy-to-use interface to query data from different sources in a single API call.
Why Graph Theory is Cooler Than you Thought
Graph Theory in Machine Learning, and How it’s Changed the Game
Causaly Raises $17m Led by Index Ventures | Marathon Venture Capital
We are thrilled to announce that Causaly has completed a new financing round of $17m
Enterprise Knowledge Graph Foundation Meeting Agenda
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GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
*GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training* by Tianle Cai, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang et al. What ...
Human Activity Recognition Models in Ontology Networks
We present Arianna+, a framework to design networks of ontologies for
representing knowledge enabling smart homes to perform human activity
recognition online. In the network, nodes are ontologies...
This is what happens when you bulk add keywords without paying attention to the details.
This is what happens when you bulk add keywords without paying attention to the details. If you’re searching for a specific result in a database or on... 43 comments on LinkedIn
Dan Brickley on Twitter
Announcing preview availability of https://t.co/587lbNTOjD - Schema Markup Validator
https://t.co/QvvuEGHtqd
Guest post from @rrlevering
#schemasmv https://t.co/AVi6ZJoC77
Seeing All From a Few: Nodes Selection Using Graph Pooling for...
Graph clustering aiming to obtain a partition of data using the graph
information, has received considerable attention in recent years. However,
noisy edges and nodes in the graph may make the...
The New InfiniteGraph is Available
With a Free 50GB Download...