neo4j-graph-renderer
Joanna Bitton created neo4j-graph-renderer – a React component that can be used to render a Neo4j graph. Since neo4j does not provide a way to render its graphs, I’ve created a react component that can be...
Category: Graphs and Data Stores
Neo4j-sparql-extension-yars
Łukasz Szeremeta created neo4j-sparql-extension-yars – a Neo4j unmanaged extension that provides RDF storage and SPARQL 1.1 query features. Distributed under the GNU General Public License version 3 license. Link to GitHub
Graph NLU: Natural Language Understanding with Neo4j
Graph NLU – a project he built to understand natural language dialogue in an interactive setting by representing memory of previous dialogue states using a persistent graph You can also find the code in...
Release Notes: Neo4j 3.2.2
Release Date: 07/05/2017 Neo4j 3.2.2 is a maintenance release, with important improvements. Highlights IPv6 supported for HA Make sure to not use locking index seeks with read-only Cypher queries Removed OptionalExpand from compiled Cypher...
Neo4J: Get Started
Get Started Taking the first steps with Neo4j? Read our introductory tutorials and developer guides that cover all areas of your development work. Your First Steps Getting started with Neo4j is easy. Take your...
React Movie Template application
This project contains a Node.js starter template for a Neo4j movies dataset. http://neo4jmovies.herokuapp.com This Neo4j-based node / react web app displays movie and person data in a manner similar to IMDB. It is designed to...
Getting Started with the Microsoft Concept Graph in Neo4j
By Cristina Escalante, COO of SilverLogic | March 8, 2017 Introduction What does the study of concepts (or categories, depending on your field of study) tell us about the human mind? A result of the...
Co-occurrence rate networks: towards separate training for undirected graphical models.
Towards separate training for undirected graphical models Zhemin Zhu. PhD Thesis, University of Twente, 2015 Abstract Dependence is a universal phenomenon which can be observed everywhere. In machine learning, probabilistic graphical models (PGMs) represent depen-...
cognoma- puts machine learning in the hands of cancer biologists.
cognoma : BY Daniel Himmelstein, Postdoctoral Fellow at University of Pennsylvania, in collaboration with the DataPhilly and Code for Philly meetups. This project puts machine learning in the hands of cancer biologists. BUILD A CLASSIFICATION ALOGRITHM...
Hetionet: an integrative network of disease
Daniel Himmelstein is the creator of Hetionet – an integrative network of biology, disease, and pharmacology. ‘hetnet’ is actually a word coined by Daniel to describe networks with many types of relationships Hetionet is a hetnet...