Current action recognition systems require large amounts of training data for recognizing an action. Recent works have explored the paradigm of zero-shot and few-shot learning to learn classifiers...

In graph embedding, the connectivity information of a graph is used to represent each vertex as a point in a d-dimensional space. Unlike the original, irregular structural information, such a...

Graph neural networks (GNN) represent an emerging line of deep learning models that operate on graph structures. It is becoming more and more popular due to its high accuracy achieved in many...

spectral-based subspace learning is a common data preprocessing step in many machine learning pipelines. The main aim is to learn a meaningful low dimensional embedding of the data. However, most...

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...

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

"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

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!

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

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.

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

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

Category Theory and Functional Programming If you are into graph databases - you need to check out category theory. It is going to be a 'thing'. The ...

Our #Yahoo! Knowledge Graph version of #Wikipedia entity embedding is now publicly available. This will be the version we use to trigger the related entity search for knowledge panels in Yahoo! Search, try it if you need general entity embedding in any task. @wikiworkshop https://t.co/eB9H6ai2zI— Chien-Chun Ni (@saibalmars) September 2, 2020

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👋 Hello, I hope you are all doing well during the lockdown.

based diagnosis of disease, and drug repurposing. Integrating data and knowledge is a formidable challenge in biomedical research. Although new scientific findings are being discovered at a rapid pace, a large proportion of that knowledge is either locked in data silos (where integration is hindered by differing nomenclature, data models, and lice

Check it. Explainable AI: From the peak of inflated expectations to the pitfalls of interpreting machine learning models https://t.co/AmS9dZz1Iv via @ZDNet & @linked_do #tech #digital #data #business pic.twitter.com/Lvxx7MTcsO— Kohei Kurihara -DataPrivacy for Fighting Covid-19- (@kuriharan) August 24, 2020