GraphNews

Knowledge graph embedding approaches represent nodes and edges of graphs as mathematical vectors. Current approaches focus on embedding complete knowledge graphs, i.e. all nodes and edges. This...

We present CoDEx, a set of knowledge graph Completion Datasets Extracted from Wikidata and Wikipedia that improve upon existing knowledge graph completion benchmarks in scope and level of...

Systemic analysis of available large-scale biological and biomedical data is critical for developing novel and effective treatment approaches against both complex and infectious diseases. Owing to the fact that different sections of the biomedical data is produced by different organizations/institutions using various types of technologies, the data are scattered across individual computational resources, without any explicit relations/connections to each other, which greatly hinders the comprehensive multi-omics-based analysis of data. We aimed to address this issue by constructing a new bi...

Knowledge graphs are structured representations of real world facts. However, they typically contain only a small subset of all possible facts. Link prediction is a task of inferring missing facts...

Knowledge graphs represented as RDF datasets are integral to many machine learning applications. RDF is supported by a rich ecosystem of data management systems and tools, most notably RDF...

In a RuleML technical memo; Graph-Relational Data, Ontology, Rules ; Harold Boley points out that ...

Building on recent work that identified human host proteins that interact with SARS-CoV-2 viral proteins in the context of an affinity-purification mass spectrometry screen, we use a machine learning-based approach to connect the viral proteins to relevant biological functions and diseases in a large-scale knowledge graph derived from the biomedical literature. Our aim is to explore how SARS-CoV-2 could interfere with various host cell functions, and also to identify additional drug targets amongst the host genes that could potentially be modulated against COVID-19. Results are presented in...

An earlier article, Fact-Based AI — Improving on a Knowledge Graph, I provided a vision for Fact-Based Modelling’s future in AI while…

Check out this interview with Charlie Beveridge from Accenture on navigating the future of artificial intelligence with knowledge graphs.

Elena Williams https://2020.pycon.org.au/program/A878CA Relational and NoSQL DBs have ruled the roost for a couple of decades now, but in real life there's more to data than just tables or key-pairs. Graph DBMS technology has been coming along for the last decade-or-so and is now quite mature. Everyone wants one, just ask a Fortune 500 company. I mean: why have a table when you can have a knowledge graph? Why not be able to whip up a recommendations engine (or indeed a fraud detector) in a few minutes? Graph databases store data in Graphs -- that is NOT chart-visualisation nor syntax standa...

"What if we had no Wikipedia? Domain-independent Term Extraction from a Large News Corpus" identifying “wiki-worthy” terms in a massive news corpus, with minimal dependency on actual Wikipedia entries.(Bilu et al, 2020)https://t.co/wEts0vt9tl pic.twitter.com/7Zv3AnPZXt— WikiResearch (@WikiResearch) September 18, 2020

AI bots do marvelous things such as facial recognition, document analysis, and creating false videos of world leaders singing pop songs. AI bots, however, are only as smart as they are programmed. …

As requested , here are a few non-exhaustive resources I'd recommend for getting started with Graph Neural Nets (GNNs), depending on what flavour of learning suits you best. Covering blogs, talks, deep-dives, feeds, data, repositories, books and university courses! A thread 👇 pic.twitter.com/el1kb8rS4G— Petar Veličković (@PetarV_93) September 17, 2020

You see these great looking Google results? The ones with all the bells and whistles? These are called rich results and you can get them too!

My engineering friends often ask me: deep learning on graphs sounds great, but are there any real applications? While Graph Neural Networks are used in recommendation systems at Pinterest, Alibaba and Twitter, a more subtle success story is the Transformer architecture, which has taken the NLP world by storm. Through

Graphs are a natural and fundamental representation of describing the activities, relationships, and evolution of various complex systems. Many domains such as communication, citation,...

Google introduces a personalized entity repository, similar to a user-specific knowedge graph to predict actions and suggestions for users of Google.

Interview with Giovanni Campagna, one of the Almond principal developers

Get this introductory book on graph databases to learn the basics of the fastest-growing database technology and get started on your own graph project.

Ontotext has released the 9.4 version of GraphDB with the main objective to lower the cost of creating and consuming knowledge graphs. Read further.

Use KronoGraph, the time visualization toolkit for JavaScript developers, to build interactive, scalable timeline tools to explore evolving relationships and events.

I’m Azeem Azhar. I convene Exponential View to help us understand how our societies and political economy will change under the force of rapidly accelerating technologies. Some of my latest commentary: A short history of knowledge technologies How the roadmap for self-driving cars has led them up a blind alley

Using Python to create a graph in Neo4j based on real-world trade data we derive insights around trading behavior of different regime types

Apple Search Starts with Siri Search In 2012, I wrote about the Apple Siri Patent application. The patent I wrote about was Intelligent Automated Assistant. In coming out with Siri, an automated assistant, Apple was creating something much more complex than just a search engine. As the patent filing says: Unlike search engines which only […]

Just launched TerminusHub on Hacker News. Would really appreciate upvotes - in the 'Show HN' section. TerminusHub, Revision Control for Structured Data...

Walder offers an easy way to set up a website or Web API on top of decentralized knowledge graphs. - KNowledgeOnWebScale/walder

As easy to use as a word document or bulleted list, and as powerful for finding, collecting, and connecting related ideas as a graph database. Collaborate with others in real time, or store all your data locally.

All right, I'll admit, this is clickbait. I generally avoid writing "[Fill in Ordinal Number of Bullet Points Here] [Cool|Neat|Amazing|Similar Token] [List of X Thing]" articles, because they usually have no real value to them, but just for once, given the subject matter, I'll succumb to the temptat