GraphNews

Many real-world tasks require understanding interactions between a set of entities. Examples include interacting atoms in chemical molecules, people in social networks and even syntactic interactions between tokens in program source code. Graph structured data types are a natural representation for such systems, and several architectures have been proposed for applying deep learning methods to these structured objects. I will give an overview of the research directions inside Microsoft that have explored different architectures and applications for deep learning on graph structured data. Se...

In this short technical blog, I will show you how to use GSQL to search a graph for all the occurrences of a small graph pattern. We call this pattern matching. Consider the problem of matching a pattern of vertices and directed edges in a...

limitless scalability.RDF and the Semantic web, w

Few years ago I decided that one day I would create a Graph Technology Landscape map, which would be useful for everyone who wants to discover the playe...

Sep 4 · 4 min read As a part of writing a book with Dr. Matthias Broecheler, I spent time talking to dozens of graph users from around the world.

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Moving data between semantic and property graphs

When developing web applications with frameworks like Vue.js the best approach is to subdivide it into well-defined and reusable components for the user...

Graphileon joins CovidGraph, an initiative of graph enthusiasts and companies with the goal to build a knowledge graph with relevant information about the COVID-19 virus.

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(Submitted on 21 Feb 2020) Abstract: Knowledge graphs have proven to be extremely useful in powering diverse

Graphcore CEO Nigel Toon discusses his company's computer processor and opportunities to disrupt the computer chip industry. He speaks with Bloomberg's Caroline Hyde on the sidelines of Bloomberg's Sooner Than You Think conference in London. (Source: Bloomberg)

Ontotext announces the release of GraphDB 9.0, open-sourcing GraphDB front-end and engine plugins to empower the developers of knowledge graph solutions

Ontotext releases GraphDB 9.2 featuring the anticipated support for RDF*/SPARQL* and improvements in the plug-ins for semantic similarity and versioning.

GraphDB 9.3: optimized support for arbitrary path length in SPARQL brings quicker discovery of relationships in knowledge graphs

Much of what Graph databases revolve around deals with classification. This alone can be quite challenging - learn more on the G DATA TechBlog!

2) from worldwide labs, the Graphen team, in conjunction with Columbia University, is able to align the genome of viruses, look for the canonical form of each gene location, and identify the exact variant(s) of a virus. Each virus has nearly 30k bases with each position represented by one of ATCG, the cDNA of virus. A virtual Canonical form sequence was determined independently in each position, not based on a single virus. In the Canonical form, the genomic length of a virus is 29,816. The letter of each position of the Canonical form was independently determined by the consensus of all sequenced viruses. Genome sequences need to be first aligned. The max position number after alignment is 30,532 which includes some head/tail/empty holes. After the canonical form is available, for each virus, we can then identify its exact variation in each position by comparing to the Canonical f

working individuals working overtime delivering groceries, people are taking on a role in supporting our society when we need it the most.These selfless people inspire us and we want them to know that we’re in this together. It’s time for us as a community to collaborate and do something positive.So — we invite you to join us and the global development community in an effort to unite our skills and bring some good to our world. ❤❤Let’s hack for good, together.Image source: CNN MoneyAbout Graphs4Good (GraphHack) 2020WHAT: any project that has a positive goal and can help others, qualifies. ❤WHERE: virtually, of course!

DataStax is the company behind the massively scalable, highly available, cloud-native NoSQL data platform built on Apache Cassandra™.

the task should accurately quantify the “distribution shift” in the data. Having precise control of this shift could allow us to understand the drawbacks of our learning methods, and build systems which can generalize over multiple tasks but still remember the old ones. Data distribution

and while of course there are common patterns in REST AP

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Graphs #Analytics for Fraud Detection, using Graph #NeuralNetworks for Anomaly detection. GraphSAGE is Stanford #opensource project: deep neural network-based NRL toolkit, implemented in Tensorflow, making it ideal to develop an anomaly detection system

A Developer’s Log

Discover graph-powered COVID-19 projects, how Neo4j is supporting these efforts, and also learn how to get involved or receive support.

Graphs (not charts and pretty pictures) are an abstraction that was first used by Euler in 1736 to solve the now famous Konigsberg problem. This mathematical abstraction has been proven to be useful in several niche domains where complex networks (graphs are also known as networks) had to be analyze

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