GraphNews

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Links: - .NET 5 minutes quickstart : https://cda.ms/mf - All quickstarts with all models: https://cda.ms/mg

Graham Ganssle, Data Science Lead at Expero, gave this introduction to Graph Convolutional Networks at a recent meetup of Austin Data Geeks / Austin AI. More graph videos coming soon! Join The Graph Community on Linkedin: https://www.linkedin.com/groups/3965793/ For expert graph consulting and implementation, visit: http://experoinc.com Abstract Is this group of delis a money laundering ring, or are they simply exchanging provolone? Why does Devin have so many Facebook friends, and I only have a handful? The answer to one of these questions is obvious (because I’m a nerd giving an ML presen...

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Real-world data is naturally connected. In this session, we provide an overview of the Graph API in Azure Cosmos DB and explain how our enterprise customers use it today to provide new insights on their data. You can query the graphs with millisecond latency and evolve the graph structure and schema easily. We also cover customer cases that currently leverage graph databases in their day-to-day workloads.

Scientists of AI at Google's Google Brain and DeepMind units acknowledge machine learning is falling short of human cognition and propose that using models of networks might be a way to find relations between things that allow computers to generalize more broadly about the world.

literally as well as figuratively (through investments, supplying

AI Business is dedicated to bringing relevant information regarding AI in the enterprise

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Researchers at IBM describe in a newly published paper an AI system that can synthesize image labels from only a few examples.

ArangoDB, an open source native multi-model database, is adding a new search feature to let developers efficiently interact with multiple data models by using just one technology and one query language. IDN speaks with ArangoDB CTO Dr. Frank Celler.

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Read about why and how knowledge graph technology helps build networks of interwoven digital objects in the world of cultural heritage.

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Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for all applications of artificial intelligence. The development of competences and experts in th

We are going to show how we import the W3C Organizational Ontology into Neo4j using the neosematics tools.

like experience for quickly importing CSV data into Stardog. To get started, just choose a database under Studio’s”Databases”tab and click on”ImportCSV.” Studio’s wizard will extract the headers (if any) from the CSV file you supply and will let you choose both a name for the class of data that the CSV represents(i.e.,the type of thing to which each row of the CSV corresponds) and the column that should be used for generating unique identifiers for instances of that class. To help you choose a truly unique identifier, the wizard will also show you just how distinct the data in each column of the CSV is, and will indicate whether or not the column you’ve chosen is likely to be a good one with respect to data integrity. Data Exploration

"We propose constructing one #knowledgegraph per query & show this method compresses information and reduces redundancy" > Improving long-form question answering by compressing search results / Angela Fan @facebookai h/t @aaranged https://ai.facebook.com/blog/research-in-brief-training-ai-to-answer-questions-using-compressed-search-results/

Learn about how AstraZeneca visualized patient journeys, answered important questions about prescriptions and diagnoses, and improved patient outcomes.

This article looks at the knowledge graphs of five diverse tech companies, comparing the similarities and differences in their respective experiences of building and using the graphs, and discussing the challenges that all knowledge-driven enterprises face today. The collection of knowledge graphs discussed here covers the breadth of applications, from search, to product descriptions, to social networks.

Five diverse technology companies show how it's done.

.@TDataScience talks about inference on #SemanticWeb and how to apply in a local #graphDB. What is Inference? What is it used for? Types of the procedure, Graph #Database & #Ontology, Inference in a Database #knowledgegraph #semantics #tutorial

After more than a decade, the supply-driven approach to publishing public (open) data has resulted in an ever-growing number of data silos. Hundreds of thousands of datasets have been catalogued and can be accessed at data portals at different administrative levels. However, usually, users do not think in terms of datasets when they search for information. Instead, they are interested in information that is most likely scattered across several datasets. In the world of proprietary in-company data, organizations invest heavily in connecting data in knowledge graphs and/or store data in data ...

Cicero is an #AI platform used to reduce reporters’ manual work while helping find connections, providing more transparency to readers. When a #journalist searches one of the three output options is a #knowledgegraph @gartht1 h/t @aaranged #media #tech

Virtual assistants do their jobs better thanks to Wikidata, which aims to (eventually) represent everything in the universe in a way computers can understand.

Discover how the big data company Thomson Reuters used Neo4j to develop a real-time intelligent graph recommendation engine for financial analysts.

Part 3 in a series about Knowledge Graphs