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

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

Managing multiple truths in #datamodeling, #ontologies & #knowledgegraphs by @palexop #semantics #vagueness #datascience #dataengineering #EmergingTech #dmzone #presentation

This article shows how an RDF Graph CRUD application can be rapidly developed, yet without losing the flexibility that HTML5/JavaScript offers, from which it can be concluded that there is no reason preventing the use of RDF Graphs as the backend for production-capable applications.

Gain a basic understanding of graph-based meta data management in enterprise data governance with Apache Atlas as a prime example.

This article takes a look at insight into evaluating a graph database gained from benchmarking different graph databases. Also explore loading capabilities.

Enables Users to Experience the World’s Fastest Graph Analytics Platform Designed to Unleash the Power of Interconnected Data for Deeper Insights and Better Outcomes

Alethio’s data scientists dig into the Ethereum blockchain to identify the major players across the transaction network. Leveraging the…

Watch the GraphConnect presentation by Dom Davis, cofounder of Tech Marionette, to discover the benefits of building a meta graph model for your domain.

Discover Neo4j Bloom, the latest product from the Neo4j team. This graph data visualization tool helps traditional Neo4j users communicate with their non-technical peers in a simple manner that reveals and explains the concepts of data connectedness for all people, regardless of technical background.

Discover a new way to visualize and explore your connected data with SemSpect: a unique approach to graph visualization that doesn't depend on using random or best-guess Cypher queries in order to explore your data's meta-graph and that is compatible with Neo4j (including RDF datasets).

Discover why your organization is a knowledge graph is essentail to build a competitive advantage with a graph dabase and machine learning algorithms.

Neo4j tunes its graph engine for AI applications - SiliconANGLE

For the milestone of the 3.4 release, we’ve implemented a set of information retrieval features exposed via new database object View.

I usually mention both as unique/key features of RDF: global identifiers and zero-cost merge— Martynas Jusevicius (@namedgraph) June 8, 2018

TigerGraph has brought forward a free Developer Edition of its graph analytics platform for lifetime non-commercial use. But, please, what is graph analytics? As defined nicely here by Hitachi ...

SAN FRANCISCO, May 2, 2018 -- Neo4j, the leading platform for connected data, today announced Neo4j 3.4, which includes horizontal scaling, performance

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

Bye Bye Silos! Those who stay on their islands will fall back. This statement is valid on nearly any level of our increasingly complex society, ranging from whole cultural areas down to single individuals.

Stardog 5.1 adds support for GraphQL, an expressive path query SPARQL extension, and stored functions.

Learn how to find similar items in the Knowledge Graph with machine learning.

A knowledge graph is the only realistic way to manage enterprise data in full generality, at scale, in a world where connectedness is everything.

by Dr. Xu Yu, CEO and Dr. Victor Lee, Director of Product Management [Excerpted from the eBook Native Parallel Graphs: The Next Generation of Graph Database for Real-Time Deep Link Analytics] Until recently, graph database designs fulfilled some but not all of the graph analytics...

Recently RedisGraph published a blog [1], comparing their performance to that of TigerGraph’s, following the tests [2] in TigerGraph’s benchmark report [3], which requires solid performance on 3-hop, 6-hop, and even 10-hop queries. Multi-hop queries on large data sets are the future of graph analytics....