GraphNews

Semantic standards have been with us since the birth of the web, when it became clear to inventors of the web like Tim Berners-Lee and many others that meaning could be systematically captured, organized, and exploited to do valuable tasks. Since then, the idea of applying formal semantics to enterprise data has come and faded […]

At the heart of things, an enterprise knowledge graph supports decision and process augmentation based on linked data. These models of knowledge domains are created by subject matter experts with the help of machine learning algorithms. They live as virtual data layers on top of existing databases or data sets to link both structured and unstructured data at scale and across disparate data silos.

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In just six months since its release, Google’s pretrained model BERT (Bidirectional Encoder Representations from Transformers) has become…

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Working for over two decades in Business Intelligence and Analytics nothing has bothered me more than being tied to a relational model.

Role of Augmented Analytics in Future !! Insight generation is changing (and That’s a Good Thing) Have you ever been in situation when you need quick insigh…

Augmented analytics tools, NLP search and graph analytics are the top trends for 2019 and beyond. Experts say augmented analytics and NLP are transforming how enterprises consume data and derive in...

/PRNewswire/ -- Aurea, the company behind some of the world's greatest customer and employee experiences, including Jive's collaboration solution, today...

Apply web scraping bots , computational linguistics, and natural language processing algorithms to build knowledge graphsContinue reading on Towards Data Science »

#Amazon #NLP service for #healthcare, Comprehend Medical, can now link information to medical #ontology. It's designed to understand relationships between things like dosage & conditions, improve medical outcomes & care #knowledgegraph #innovation

AWS Data Migration Service (DMS) now supports migrating graph data from relational sources to Amazon Neptune. The AWS Database Migration Service (AWS DMS) enables you to migrate data from one data source to another. Using relational databases as source and Neptune as destination allows customers to copy their connected data into Neptune for graph queries.   Customers using both relational and graph databases today manually load their data into Neptune. DMS minimizes the manual effort to carry out the workflow. Using DMS, you can configure a destination endpoint to existing Neptune databases. DMS will carry out a full copy of data from relational databases to Neptune. The DMS workflow allows you to target either a RDF model or a property graph model by specifying the appropriate mapping file for each data model. DMS version 3.3.2 supports Amazon Neptune as the destination endpoint. You can configure DMS using the AWS Management Console, AWS SDK or CLI. You will be ch

The Azure Cosmos DB team is excited to announce version 3.0 of the .NET SDK, now in public preview and open sourced on GitHub!

Cosmos DB's entry level pricing has come way down, opening up the service to a much broader audience. And Azure Machine Learning gets new versatility, including usability from virtually all Python-language programming environments.

We're excited to announce the public release of Akutan, a distributed knowledge graph store, under the Apache 2.0 open source license. Akutan is the result of four person-years of exploration and engineering effort, so there's a lot to unpack here! This post will discuss what Akutan is, how it's implemented, and why we've chosen to release it as open source.

.@NebulaGraph is a new #opensource #GraphDB, claiming to be capable of hosting super large scale graphs w/ dozens of billions of nodes, trillions of edges, milliseconds of latency. Inspired by #Facebook project Dragon, featured on page #1 on @HackerNews

Identifying a #propaganda bot network with graph #analytics #disinformation #socialmedia #twitter #indonesia @bellingcat h/t @Linkurious

The growing interest in making use of Knowledge Graphs for developing

Recently, link prediction algorithms based on neural embeddings have gained

Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. Neptune supports the W3C’s graph model RDF, and its query language SPARQL. SPARQL 1.1 Federated Query specifies an extension to SPARQL for running queries distributed over different SPARQL endpoints.

Designing, implementing, and leveraging a Enterprise Knowledge Graph is daunting at first. Read on to learn where to begin, and what factors to consider.

Map your employees’ relationships to improve performance.

How to simplify your GraphQL gateway with a change of perspective

I had the chance to attend Strata Data in San Francisco this week and talk to data engineers who are struggling under the burden of decades of legacy application-centric development approaches in an era when companies should be becoming data centric. Here's a way to scale up a data-centric code qual

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This document provides an overview of two modeling strategies/patterns used for building knowledge graphs and triplestores of core biological ‘knowledge’ (e.g. relations between genes, chemi…

With AgensGraph, an Education Service Company 34-years in the Making Builds a Big Data Graph Database for Education

Last week I was part of team from Optum ventured out to Stanford University in Palo Alto CA for a three-day conference sponsored by the…