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.

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.

AI is in its infancy and cannot be left unattended. Whether unintentional or by malicious design, algorithms behaving unexpectedly are now a fact of life.

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.

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....

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

Until now the only way to run Graph Algorithms on Neo4j has been to learn Cypher. The Graph Algorithms Playground changes all that.

This is what the resultant 100 retail outlet isochrone map looks like, built using Spatia and @rapidsai #cuGraph SSSP using @OrdnanceSurvey Open Roads as road graph + drive times estimated from @transportgovuk road stats #opendata cc @puntofisso pic.twitter.com/rGhDinkaVX— John Murray (@MurrayData) May 28, 2019

.@jQAssistant is a #QA tool which allows definition & validation of project specific rules on a structural level. Built upon #Neo4j #graphdatabase, can be plugged into build process. Now w/ #PlantUML class diagrams #dataviz #softwareengineering

Visualize Kafka Streams with Neo4j by taking any data, turning it into a graph, leveraging graph processing, and piping the results back to Apache Kafka, adding visualizations to your event streaming applications.

.@DDIAlliance releases XKOS v1.2 (Extended Knowledge Organization System) specification →facilitates sharing & management of statistical classifications.(For building #Semantic Taxonomies to tag Datasets & #DataScience outputs)https://t.co/HZD1nl5Nu0#BigData #Ontologies #RDF pic.twitter.com/DDYbHqCvm7— Kirk Borne (@KirkDBorne) June 21, 2019

Graphs are an excellent way of encoding domain knowledge for your business data. One of the popular databases for graphs is Neo4J and I…

When we used to think about data, it was most often in regard to where data was going to be stored and how we would manage it. Yes, files worked for a while, but when manipulating data became an important business priority across industries, the “file” solution didn’t work so well anymore. To meet these increasing demands, applications were designed and developed, addressing data storage and manipulation needs simultaneously — thus, the “database” was born. Today, data is viewed quite differently. Beyond data manipulation, organizations are focusing on mining their data for more visibility into and a deeper understanding of the intelligence within that data. Utilizing the insights acquired from their data to help make informed business decisions is a key priority for business leaders and a major concern in the development, evolution, and adoption of database solutions. A new term emerged in the industry — digital assets. That data the world has been obsessing over.

Discover what's new in the 3.5 release of the Neo4j graph database, including a Go language driver, full-text search and indexing, TLS encryption and more.

based Gruff Drives Infinite Data Integration, Holistic Insights and Complex Reasoning

Graphs are common #data structures to represent #connecteddata. To use graphs with #deeplearning, we use graph embeddings, a low dimension representations which helps generalize input data. Node2Vec aims to preserve network neighborhoods #datascience #AI

https://douroucouli.wordpress.com/2019/05/10/obographviz-0-2-2-released-now-with-visualization-of-equivalence-cliques/

Keynote talk given at the 41st European Conference on Information Retrieval (ECIR 2019)

Technology research and analyst house Bloor Research places Ontotext as champion among RDF graph providers in its latest update on the graph database market

Easily build intelligent globally distributed apps running at planet scale with Azure Cosmos DB.

Learn advanced Cypher queries for one approach to analyzing data inconsistencies directly in your flexible and forgiving Neo4j graph database.