GraphNews

Alan Morrison's answer: You’re not generating a graph as much as you are seeding, nurturing, harvesting and consuming one. You’re putting in place a cyclical, organic process to allow the graph to grow, become useful, evolve, thrive, and—ideally—marry up with other graphs, the combination of whic...

How simple structured data trumps clever machine learning

Posted by Jakub Łącki and Vahab Mirrokni, Research Scientists, Google Research Graphs are useful theoretical representations of the co...

Knowledge Graph Extension for Python - Team Project 2020 @ Uni Mannheim - om-hb/kgextension

When a new technology emerges, financial services firms often are among the first adopters. Anything that can provide banks, investment houses, or

We are proud to announce that Triply is going public, by giving away a limited number of free accounts for TriplyDB. This is the first time…

Why Question-Answering Engines? The search only for documents is outdated. Users who have already adopted a question-answering (QA) approach with their personal devices, e.

SpikeX - SpaCy Pipes for Knowledge Extraction • A collection of pipes ready to be plugged in a spaCy pipeline. It aims to help in building knowledge extraction...

We launched Stardog Free today, offering you the flexibility to explore Stardog for your project without commercial limitations. Check it out and enjoy...

This week SambaNova landed $676 million in Series D funding, making it the best-funded AI startup in the world. For many of my colleges…

Start with Graph Neural Networks from zero and implement a graph convolutional layer in Pytorch

For regular readers of the (lately somewhat irregularly published) The Cagle Report, I've finally managed to get my feet underneath me at Data Science Central, and am gearing up with a number of new initiatives, including a video interview program that I'm getting underway as soon as I can get the l

Nicole Buckenwolf use ontologies and taxonomies to organize the product information that you see at businesses like Amazon and Etsy.

SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization • A subgraph extraction module that can efficiently anchor ...

In late November the U.S. Federal Drug Administration approved Benevolent AI’s recommended arthritis drug Baricitnib as a COVID-19…

Helpful juxtaposition of various modelling paradigms. Thoughtprovoking, too, when you look at the column to the right. Even though things seem to be in... 16 comments on LinkedIn

QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering - The problem of answering questions using knowledge from pre-trained...

Drivine - Graph Database Client for Node.js & TypeScript

Of course, every thing “isa” thing

What if two of the hottest graph frameworks come together? You better come to the party! Leverages the flexibility of GraphQL in the frontend with the ... 16 comments on LinkedIn

On the role of knowledge that is structured, explicit and intelligible in providing a path toward higher machine intelligence

Apollo GraphQL has updated its Apollo Federation offering, making it more accessible to a wider range of developers using different tools.

AUSTIN, TX – April 06, 2021 – Katana Graph, a high performance scale-out graph processing, AI and analytics company, announced today that it has optimized its graph engine for the new 3rd Gen Intel Xeon Scalable processor and memory systems. Katana Graph can now take advantage of the latest generation Intel Xeon Scalable processors and […]

The future of search is the rise of intelligent data and documents. Way back in 1991, Tim Berners-Lee, then a young English software developer working at CERN…

Is it me or the Twitter graph and the LinkedIn graph feel a bit disconnected? I personally tend to interact more with the first and that's why I have the impression that the second might be missing out on some of the nice and "graphy" content that I've been producing lately. This article is just a c

Linked Data is a universal approach for naming, shaping, and giving meaning to data, using open standards. It was meant to be the second big information

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Building scalable semantic retrieval from image, text, graph, and interaction data

Relational databases schemes are essentially driven by normalization, not by real-world relationships. One of my longest SQL query has beaten 4000 lines... 12 comments on LinkedIn