GraphAware Blog

Find out what's new in the Neo4j world

Spring Boot Actuator’s Neo4jHealthIndicator

25 Nov 2017 by Eric Spiegelberg Neo4j Spring

Spring and Spring Boot have become the Swiss Army knife of Java software development, offering dozens of useful modules across a wide range of concerns.One such module is Spring Boot Actuator, a sub-project of Spring Boot, that offers built-in, production-grade functionality to help monitor and interact with an application. Numerous endpoints are included that provide a wealth of information that, among others, include auditing, configuration, environment, and health details.The /health EndpointOne particularly useful endpoint is /health, which displays information on the application’s overall health and can be used by monitoring software to generate alerts should a system component become unavailable....

Cybersecurity & Graph Technology: An Excellent Fit

24 Oct 2017 by Eric Spiegelberg Neo4j Security

We are becoming increasingly dependent on technology. Yet, without diligent attention paid to cybersecurity, technology is vulnerable to unauthorized access, change or even destruction. These vulnerabilities pose threats to our individual and collective safety, security and human and economic well-being.Cybersecurity is therefore a vitally important global issue with substantial consequences that depends on safe, stable, and resilient security of our data, devices, and systems.Equifax: The BreachThe latest major cybersecurity incident was publically revealed when Equifax, a US-based consumer credit reporting agency that assimilates and analyzes the financial health of more than 820 million consumers and 91 million businesses globally, announced a...

7VORTEX: Systems Thinking Powered By Graphs

15 Oct 2017 by Miro Marchi Neo4j Graph Visualization Connected Data Analytics

The success of many enterprises greatly depends on their ability to gather useful information and process it in a timely manner. Automation is essential and so is presentation, giving tangible feedback, to decision makers. This is where technology reaches out to management, where science and design are combined to put the right people in the position of making better and more sustainable choices.Decision making is often a very complex task. Outcomes depend on a multitude of interactions between variables, actions, and actors at play in multiple contexts. While emphasis on individual aspects or subsets of interactions is very important, information...

Efficient unsupervised keywords extraction using graphs

03 Oct 2017 by Alessandro Negro, Vlasta Kůs, Miro Marchi, Christophe Willemsen Neo4j NLP Knowledge Platform Cognitive Computing

Companies of any size have to manage and access huge amounts of data providing advanced services for their end-users or to handle their internal processes. The greater part of this data is usually stored in the form of text. Processing and analyzing this huge source of knowledge represents a competitive advantage, but often, even providing simple and effective access to it is a complex task, due to the unstructured nature of the textual data. This blog post will focus on a specific use case: provide effective access to a huge set of documents - later referred as a corpus -...

Reverse Engineering Book Stories with Neo4j and GraphAware NLP

24 Jul 2017 by Christophe Willemsen Neo4j NLP Cypher

A book tells us a story, but for a computer it is a wall of text. How can we use graphs and NLP to help our machines make more sense of a story?Our example comes from the A Song of Ice and Fire books, aka Game of Thrones. We converted the e-books (epub) to text-files and used a small python program to split them into chapters, paragraphs, and sentences.So a book turned into this model :GraphAware NLPGraphAware NLP Framework is a project that integrates NLP processing capabilities available in several software packages like Stanford NLP and OpenNLP, existing data sources,...

Relevant Search Leveraging Knowledge Graphs with Neo4j

05 May 2017 by Alessandro Negro Neo4j Elasticsearch Knowledge Graph Search NLP Recommendations

“Relevance is the practice of improving search results for users by satisfying their information needs in the context of a particular user experience, while balancing how ranking impacts business’s needs.” [1]Providing relevant information to the user performing search queries or navigating a site is always a complex task. It requires a huge set of data, a process of progressive improvements, and self-tuning parameters together with infrastructure that can support them.Such search infrastructure must be introduced seamlessly and smoothly into the existing platform, with access to all relevant data flows to provide always up-to-date data. Moreover, it should allow for easy...

What’s New in Neo4j Databridge [April 2017]

27 Apr 2017 by Vince Bickers Neo4j ETL Databridge

Since our first post a few months back, Neo4j-Databridge has seen a number of improvements and enhancements. In this post, we’ll take a quick tour of the latest features.Streaming EndpointAlthough Databridge is primarily designed for bulk data import, which requires Neo4j to be offline, we recently added the capability to import data into a running Neo4j instance.This was prompted by a specific request from a user who pointed out that in many cases people want to do a fast bulk-load of an initial large dataset with the database offline, and then subsequently apply small incremental updates to that data with...

Bridging similarity islands in recommendation systems with Neo4j

08 Mar 2017 by Miro Marchi Neo4j Recommendations

Recommendation engines are a crucial element in the global trend towards a push-based web experience and away from a pull-based one. They provide the ability to personalize content offered to each user by predicting the interest the user will have in the recommended items. This is not only a powerful business tool for content providers, but also a vital improvement to the user experience. In today’s world where the volume, interdependence, variety and speed of information is overwhelming, recommendation engines can significantly reduce the gap between us and what we search for. Indeed, these engines are used even to enhance...

GraphAware at GraphConnect San Francisco 2016

25 Nov 2016 by Miro Marchi Neo4j Conference GraphAware

Last month, the 5th edition of GraphConnect San Francisco took place at the Hyatt Regency SF. It was the biggest graph technology event ever and GraphAware proudly contributed as a sponsor, with one main talk, two lightning talks and our GraphHero stand 。^‿^。 This edition’s big announcement was the upcoming new landmark release of Neo4j 3.1, “The database for the connected enterprise”, which introduces a new state-of-the-art clustering architecture and new security architecture to meet enterprise requirements for scale and security. There will be a lot to say about this release, but you can already try the beta release as...

Introducing GraphAware Databridge: Graph Data Import Made Simple

10 Oct 2016 by Vince Bickers Neo4j ETL Databridge

IntroductionUntil now, Neo4j users wanting to import data into Neo4j have been faced with two choices: Create Cypher statements in conjunction with Cypher’s LOAD CSV or use Neo4j’s batch import tool.Each of these approaches has its strengths and weaknesses. LOAD CSV is very flexible, but you need to learn Cypher, it struggles with large volumes of data and is relatively slow.On the other hand, Neo4j’s batch import tool is extremely efficient at processing large data volumes. You don’t need to know any Cypher, but the input files usually need to be manually generated beforehand. Being a simple CSV loader, it...