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Why are data efforts still starting with field sizes in rows and columns?

Recent successes in training word embeddings for NLP tasks have encouraged a

OrientDB v 3.1 includes Materialized Views as a new feature.

Learn all about Neo4j's new strategic partnership with Google Cloud that delivers Neo4j as a fully managed service deeply integrated with Google Cloud Platform.

The good, the bad and the weird

Contrary to some other data models, RDF is not bound by a single serialization format. Triple statements (the data atoms of RDF) can be serialized in many ways, which leaves developers with a possibly tough decision: how should I serialize my linked data?

A hunger inducing dataset

If we wish to foresee the future of mathematics, our proper course is to study the history and present condition of the science. Henri…

1. Welcome to ServerlessToronto.org

a totally different way to see data, with endless possibilities!

#Neo4j #GraphDB has added sharding @adamcowley shows when and how to use it #softwareengineering #data #tech #opensource #tutorial [LINK]https://adamcowley.co.uk/neo4j/sharding-neo4j-4.0/ [LINK]https://neo4j.com/docs/operations-manual/4.0-preview/images/fabric-single-instance.png

By treating reifications, assertions about assertions, as first-class objects in the Semantic Web, the idea of interchange between property and semantic graphs and the ability to work with graphs using a much broader set of tools opens up.

Automatic radiology report generation has been an attracting research problem

DBpedi

We’ve been asked to comment on the applicability of Knowledge Graphs and Semantic Technology in service of a couple of common use cases. We will draw on our own experience with client projects as well as some examples we have come to from networking with our peers.

And how Graph Theory can prove itContinue reading on Towards Data Science »

The Linked Data ecosystem and RDF as its graph data model have been around for many years already. Even though there is an increasing interest in knowledge graphs, many developers...

A knowledge scientist is a person who builds bridges between #business requirements, questions, and #data. The goal is to document knowledge @juansequeda #AI #machinelearning #businessintelligence #analytics https://www.infoworld.com/article/3448577/who-should-be-responsible-for-your-data-the-knowledge-scientist.html

According to Reinforcement Knowledge Graph Reasoning for Explainable Recommendation

As most of the global workforce goes remote in 2020, businesses and budgets are changing due to a decrease or increase in site traffic. Since this pandemic is new for marketers and organizations, there isn’t exactly a marketing blueprint but one channel is proven to outlast pandemics: Search Engine Optimization (SEO).

Big data combined with advances in data science approaches have provided a valuable opportunity for the pharma industry to uncover…

19 pandemic is impacting data and analytics strategies in profound ways. Experts explain what your company should be doing right now.

Why graph databases are becoming mainstream and their connection to AI, ML and big data use cases.

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Graph databases are becoming more important to analytics by offering a capability to store relationships and perform unique algorithms.

This is a continuation of the discussion that originates on this StackExchange post, about recommender systems using knowledge graphs(KGs). For those who might not prefer reading the original post,...

Why is it so hard to standardize a Graph Query Language ? It is because graph databases are strongly dependent on the data model and the physical layer... 37 comments on LinkedIn

A knowledge base can be thought of as a data encyclopedia that’s specific to an organization, subject domain or location.

A critical distinction between machines and humans is the way in which we reason about the world: humans through high order semantic abstractions and machines through blind adherence to statistics.