GraphNews

Our interview with Teodora Petkova, sharing her views on weaving text into the semantic web and her recent book The Brave New Text.

LinkedSDGs: linking information resources & discovering connections to #SDGs 1) upload document 2) extract key concepts 3) find links to #SDGs & relevant stats #linkeddata & knowledge extraction resources @SustDev #opendata #data #tech #sustainability [LINK]https://www.linkedin.com/feed/update/urn:li:activity:6628584405906661376/ [LINK]https://media-exp1.licdn.com/dms/image/C5622AQELLgccoCKFCw/feedshare-shrink_800/0?e=1583366400&v=beta&t=pfry2nj7rsH7Ex5cOs36op-Wdn0Y1lyvsYVUhMzEj7k

To get insights from between the lines, you can correlate and categorize the tags of StackOverflow based on the questions they are…

Ontological metadata, being machine- as well as human-, readable, can drive processes, reduce data redundancy, and can be used to surface new information through inferencing and rich querying/updates. Ontologies will enrich taxonomies and make them more useful to the organization overall.

The distinctions between machine learning and semantics are disappearing - they are both simply tools for managing the metadata associated with the data that flows through every organization and domain.

Taxonomy Development in a #LinkedData World by @aaranged @cosmicangler at @tbc_london The big idea: Because the world we live in is big and complex, we need to go about the job of taxonomy development in a way that matches that

Ahren Lehnert looks at lifecycles and versioning. The basic governance practices are common when managing taxonomies and ontologies.

One might expect to see “Long Live Taxonomy!” following the above statement just to keep the tradition going of announcing a new king, but sadly that’s not the case. Taxonomy, as we’ve known it, built it, used it, sold it and relied on it for a living for a long time, is, according to Gartner’s 2018

sized – offer products and services to help in the fight.

/PRNewswire/ -- tellic graph.C19 visualizes 12 million connections between COVID-19 and related genes, drugs, phenotypes and variants Scientists at Empire...

What is an RDF database and what it brings to the table for companies when it comes to researching, authoring and publishing content.

world problems involving networks of transactions of various nature and social interactions and engagements are dynamic and can be modelled as graphs where nodes and edges appear over time. In this post, we describe Temporal Graph Network, a generic framework for deep learning on dynamic graphs.

An open source database for data people. Join the data-centric revolution!

Machine learning reveals knowledge of materials ‘hidden’ in papers.

Learn more about text-mined knowledge graphs and see how to build one with Grakn.

Photo by AndreyPopov on iStockWe all use the Google Knowledge Graph tens of times a day, but maybe not many of us are aware to be actually querying the Graph while making a simple search on Google.When you search for something, for example, “Goldman Sachs”, what you get is a list of snippets of web pages plus an Infobox next to the search results.The Knowledge Graph behind your Google search allows to enhance the search engine with specific and possibly useful features on the “entity” you are looking for (in this case Goldman Sachs), gathered from a variety of sources. So, allegedly, Google Knowledge Graph enhances the result of our search with semantics [4].Let’s now try to consider reasoning.Now, say we are studying Goldman Sachs for some reason and we wish to know whether there is some person x in Goldman Sachs board who is the CEO of some other company y that is in the Tech field?Or in other terms, in a ‘fancy’ logic conjunctive query fashion:∃ x y board(Goldm

Knowledge graphs and their relation to taxonomies, ontologies, and other knowledge organization systems.

WHAT THIS TALK IS ABOUT My personal take on the history of human label collection ter to you

Cases of the Wuhan coronavirus have been confirmed around the globe, reminding us that the capacity to quickly develop, test and deploy new drugs is essential to save lives. Unfortunately, experts say we still are years away from a vaccine for the virus. However, a type of artificial intelligence can speed up the drug development process that already exists, but it hasn’t yet been deployed at scale.

time.Therefore, we have recognised that building a “Talent Knowledge Graph” will allow us to effectively operate in our domain as well as to fully unlock the predictive power of artificial intelligence and provide unique insights from our heterogeneous data sources.After Google’s reveal of its Knowledge Graph platform in 2012, the term has been rapidly growing in popularit

I realized that I needed to know what the constituent parts of data models really are. Across the board, all platforms, all models etc. Is there anything similar to atoms and the (chemical) bonds that enables the formation of molecules?

What’s the difference between AnzoGraph and many other graph databases on the market? This infographic highlights the many nuances between them.

The best (and new) survey on the theoretical aspects of GNNs I'm aware of. So many illustrative examples of what GNN can and cannot distinguish.

OpenAI believes that huge computing power is key driver

If information does not exist in electronic form by now in your organization, it is very likely already lost.

#knowledgegraphs need #DLTs to secure keys, DLTs need knowledge graphs to provide context & provenance. Ultimately, knowledge graphs will end up being the integration point for a number of #technologies lumped under #AI #data #EmergingTech @kurt_cagle

“You must unlearn what you have learned” (Master Yoda) The “conceptual” level

.@shivamshaz #datascientist who rules #DataScience for Good competitions on #Kaggle wants to apply expertise in #ML to solve micro-finance problems for underbanked population in developing countries using network science, graph theory, unstructured data