GraphAware Blog - Neo4j

Find out what's new in the Neo4j world

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.

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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.

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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 - identifying main concepts , organizing indexes and providing an adequate visualization.

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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 common text based search (read more about graph-aided search in our blog).

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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 we have done!

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Using NLP + Neo4j for a Social Media Recommendation Engine

04 Oct 2016 by Alessandro Negro Neo4j NLP

In recent years, the rapid growth of social media communities has created a vast amount of digital documents on the web. Recommending relevant documents to users is a strategic goal for the effectiveness of customer engagement but at the same time is not a trivial problem.

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Internationalization with CypherMessageSource, Spring and Neo4j

29 Sep 2016 by Eric Spiegelberg, Guest Author Neo4j SDN Internationalization Localization

Whether you realize it or not, the software you create has a global market. Perhaps more so than any other product in any other industry, code that may start as a small, individual effort has the potential to rapidly blossom into a product used around the world. While it is not always obvious that your application can or will have such wide usage, it is in your best interest to maximize the number of organizations and people you can reach. This means it is important to ensure your software is internationalized and localized.

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Graph-Aided Search - The Rise of Personalised Content

20 Apr 2016 by Alessandro Negro and Christophe Willemsen Neo4j Cypher Recommendations Elasticsearch

In our previous blog post we introduced the concept of Graph Aided Search. It refers to a personalised user experience during search where the results are customised for each user based on information gathered about them (likes, friends, clicks, buying history, etc.). This information is stored in a graph database and processed using machine learning and/or graph analysis algorithms.

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(Un)common Use Cases for Graph Databases

18 Apr 2016 by Michal Bachman Neo4j Beginner Modelling

At GraphAware, we live and breathe Neo4j. For three years, we have been helping customers around the world embrace this amazing technology as a solution to many interesting problems. Mainstream applications of graphs, such as real-time recommendations, fraud detection, impact analysis, and graph-aided search, have been getting a lot of media attention.

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Neo4j OGM Events - Part 1

13 Apr 2016 by Vince Bickers Neo4j OGM SDN Intermediate

As of version 2.1, Neo4j OGM will support persistence events. Although a date for the release of 2.1 isn’t known at the time of writing, we think this is an important and exciting new feature and so we’ll be writing a series of posts about it over the next few weeks to whet your appetites. In this first post we’ll take a quick tour of the new Events mechanism in the OGM, and provide some examples of how we might use it in our own applications. But first, some background…

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Securing Neo4j with GraphAware Enterprise

29 Mar 2016 by Michal Bachman Neo4j GraphAware Intermediate Security Enterprise

For most organisations, data security is extremely important. The topic comes up every single time we are training, consulting, or otherwise engaging in the world of graphs and Neo4j. At the same time, security is very difficult and time-consuming to get right and the implications of getting it wrong can be serious. In this blog post, we introduce the integration of Spring Security into Neo4j which provides important security controls and mechanisms for enterprises and governments that make use of the world’s most popular graph database.

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Expiring Data in Neo4j

15 Mar 2016 by Michal Bachman Neo4j GraphAware Intermediate

At GraphAware, we help organisations in a wide range of verticals solve problems with graphs. Once we come across a requirement or use case two or three different times, we typically create an open-source Neo4j extension that addresses it. The latest addition to our product portfolio, introduced in this post, is a simple library that automatically expires data from the Neo4j graph database.

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Processing Large Sets of Nodes with Cypher

10 Dec 2015 by Christophe Willemsen Neo4j Cypher

Iterating over large numbers of nodes using Cypher is quite a common use case in Neo4j. Typically, the reason for doing this is that we want to perform some kind of operation for each one of these nodes. In this blog post, we will use one million TestNodes and try to iterate over them in order to index their contents into a freshly created Elasticsearch index. There are three approaches we can take, two of which are quite common, but the most performant technique is largely unknown.

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Faster Recommendations with Neo4j 2.3 Triadic Selection

20 Oct 2015 by Alessandro Negro & Christophe Willemsen Neo4j Cypher Recommendations

Recently, Neo Technology announced the 2.3.0-RC1 release of their Neo4j graph database. One of the key new features is Triadic Selection built into Cypher’s Cost Based Planner. In this blog post, we will explore the Triadic Selection in detail and demonstrate how significantly it can speed up recommendations computed in Neo4j.

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Recommendations with Neo4j and Graph-Aided Search

30 Sep 2015 by Michal Bachman Neo4j Recommendations Search Elasticsearch

For the last couple of years, Neo4j has been increasingly popular as the technology of choice for people building real-time recommendation engines. Having been at the forefront of the graph movement through client engagements and open-source software development, we have identified the next step in the natural evolution of graph-based recommendation engines. We call it Graph-Aided Search.

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Object Models and Spring Data Neo4j 4

03 Sep 2015 by Luanne Misquitta Neo4j Spring SDN OGM

Drawing a graph on a whiteboard is easy and fun! Translating that graph into an object model can sometimes result in questions such as “do I have to define relationships in both participating node entities?” or “which end of the relationship should I save?”.

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Integration Testing Against Remote Neo4j

20 Aug 2015 by Adam George Neo4j Advanced GraphUnit Testing

Writing integration tests for your code that runs against Neo4j is simple enough when using the native API, but there’s not a great deal of help out there if you’re working in client-server mode. Making assertions about the shape of the graph can also be difficult, particularly if use cases involve more than a few nodes and relationships.

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Cypher: Variable Length Relationships by Example

19 May 2015 by Christophe Willemsen & Michal Bachman Neo4j Cypher

In this blog post, we’ll demonstrate how to use variable length relationships (sometimes called “variable length paths”) in Cypher using examples. We will also see when zero length relationships can be useful.

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Neo4j Events (Jan/Feb 2015)

16 Jan 2015 by Michal Bachman Neo4j Events Beginner

There is no better way to start 2015 than to learn something new. In the wake of two recent major announcements (here and here), Neo4j is as hot as ever, so it might well be the next skill you pick up or improve. Here’s a list of Neo4j events organised by GraphAware around the world in the next few weeks. We’ll be delighted to see you there!

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Using the Neo4j Browser with Embedded Neo4j

21 Nov 2014 by Luanne Misquitta Neo4j Intermediate

There are times when you have an application using Neo4j in embedded mode but also need to play around with the graph using the Neo4j web browser. Since the database can be accessed from at most one process at a time, trying to start up the Neo4j server when your embedded Neo4j application is running won’t work. The WrappingNeoServerBootstrapper, although deprecated, comes to the rescue. Here’s how to set it up.

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GraphConnect 2014 Talk

20 Nov 2014 by Michal Bachman Neo4j Conference Intermediate

Last month, I had the pleasure of speaking at GraphConnect in San Francisco, introducing the GraphAware Framework to a large audience of Neo4j users and graph enthusiasts. For those who missed the conference, the recording and slides have now been made available. Enjoy and get in touch with feedback / questions!

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Random Graph Models (Part II)

06 Aug 2014 by Vojtěch Havlíček Neo4j GraphAware Intermediate

In the first part of this short series about random graph models, we talked about why they are useful and had a brief look at two of them: Erdos-Renyi graphs and Barabasi-Albert model. In this post, we take a look at the “small world” phenomenon and another network model, namely the Watts-Strogatz model.

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Random Graph Models (Part I)

16 Jul 2014 by Vojtěch Havlíček Neo4j GraphAware Intermediate

When one obtains a graph data from a measurement on a real world network, it is sometimes useful to make comparison with a random graph. Such graph is characterised by certain degree distribution, which you can imagine to be a list of degrees of nodes present in the network. The most interesting distributions have certain functional dependence which allows one to infer what processes are dominant in formation of the network. The processes consequently characterise the relationships between the nodes.

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Happy Birthday GraphAware

03 Jun 2014 by Michal Bachman Neo4j GraphAware

Today, it is exactly one year ago since Graph Aware Limited was incorporated. It started as a one man show, whilst I was finishing my MSc. Thesis at Imperial College London. Since then, we’ve been growing slowly but steadily and will be moving to our new London office fairly soon (announcements to come). We have happy clients in London, New York, Copenhagen, Barcelona, Prague, and Accra.

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Introducing GraphAware Neo4j Framework

28 May 2014 by Michal Bachman Neo4j GraphAware Intermediate

In this short blog post, I would like to introduce the GraphAware Neo4j Framework. Its goal is very ambitious: we’d like to make it as useful for Neo4j developers, as the Spring Framework is for Java developers. The Framework aims at speeding up development with Neo4j by providing a platform for building useful generic as well as domain-specific functionality, analytical capabilities, graph algorithms, and more.

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(Big) Data Science (2013 WebExpo Talk)

23 May 2014 by Michal Bachman Neo4j Conference NoSQL

After a long wait, I finally got the opportunity to publish the recording of my graph/Neo4j talk at WebExpo Prague 2013, intentionally and somewhat misleadingly titled “(Big) Data Science”. Thanks to the organisers for making it available and see you soon at WebExpo 2014!

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Neo4j Meetup Prague

26 Oct 2013 by Michal Bachman Neo4j Meetup

We are pleased to announce the first official Czech Neo4j Meetup on 11th November 2013 at 6pm at the Czech Technical University in Prague. It is a free event: Anyone interested in learning about graph databases as well as those already using them are welcome to attend, listen to the talks, and join us for a beer afterwards. The talks will be in Czech.

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Modelling Data in Neo4j: Bidirectional Relationships

11 Oct 2013 by Michal Bachman Neo4j Modelling Beginner

Transitioning from the relational world to the beautiful world of graphs requires a shift in thinking about data. Although graphs are often much more intuitive than tables, there are certain mistakes people tend to make when modelling their data as a graph for the first time. In this article, we look at one common source of confusion: bidirectional relationships.

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