GraphAware Blog - Beginner

Find out what's new in the world of mission-critical graph analytics.

Context-aware and hybrid recommendations

Context-aware and hybrid recommendations

11 Aug 2022 by Alexandra Klacanova · 6 min read Beginner business Recommendations

So far, we have learned about collaborative filtering, content-based, and session-based recommendations. None of these approaches takes the situational context under consideration. Factors such as mood, occasion, location, company, etc., can affect user preferences and needs. Context-aware recommendations take these conditions into account to provide more relevant recommendations.

Understanding graph visualisation

Understanding graph visualisation

30 Jun 2022 by Alexandra Klacanova · 5 min read business Beginner Knowledge Graph

Graph visualisation is just what it sounds like - a visual representation of your data as a graph. A graph is a structure of objects that are connected. Thus graph visualisation is the visualisation of entities (nodes), and relationships among them.

Session-based recommendations with Graphs

Session-based recommendations with Graphs

14 Jun 2022 by Alexandra Klacanova · 6 min read Beginner business Recommendations

Graph-Powered Machine Learning has already introduced us to content-based recommendations and collaborative filtering. These are the two most used approaches to providing recommendations. However, they both need information about the users to do so. What if you do not have user information? That’s where session-based recommendations come in.

Intro to collaborative filtering

Intro to collaborative filtering

12 May 2022 by Alexandra Klacanova · 7 min read Beginner business Recommendations

Welcome back to the Graph-Powered Machine Learning book club. Now we are in the section of the book that focuses on recommendations. In the last blog, I summed up how content-based recommendations work. In the fifth chapter, the author Alessandro Negro introduces us to collaborative filtering.

What are content-based recommendations?

What are content-based recommendations?

19 Apr 2022 by Alexandra Klacanova · 7 min read Beginner business Recommendations

So far, the Graph-Powered Machine Learning book has introduced us to graphs and machine learning. The second part of the book talks about recommendations. Recommender systems (RS) gather information about users and items and provide item suggestions, bringing great value to online stores - clothing stores, bookstores, you name it. Companies like Netflix base their entire businesses on high performing recommender systems.

Big data basics

Big data basics

24 Feb 2022 by Alexandra Klacanova · 8 min read Beginner business LPG

Welcome back to the Graph-Powered Machine Learning book club. As you know by now, Graph-Powered Machine Learning is a book written by our very own Dr. Alessandro Negro. The book is a must-read for all data scientists, but it’s also a great read for everyone interested in graphs. In this blog series, I summarise the key points of each chapter and provide some more explanations useful for us less technically savvy. We learned the basics about machine learning, graphs, and why the two are a great fit in the first chapter.

Newbie guide to databases

Newbie guide to databases

15 Feb 2022 by Alexandra Klacanova · 3 min read Beginner business NoSQL

There are a multitude of databases to choose from when deciding how to store your data. They differ in complexity, scalability, data modelling possibilities they offer, and application. Let’s walk through some of the most popular databases and their differences.

5 things you should know about Knowledge Graphs

5 things you should know about Knowledge Graphs

14 Oct 2021 by Alexandra Klacanova · 9 min read Knowledge Graph Beginner Hume business

Welcome to the first blog in the business series of GraphAware blog! This series is designed for us non-techies out there. Personally, I was shocked when I found out how big and common knowledge graphs are and how often graph databases are used in today’s world - and I had first heard of them just a couple of months ago. So, for people like me, for marketers and non-tech people in business, I’ll try to open the door to the world of graphs, and their potential and take you through it step-by-step. It seems only appropriate that we start with...

Build your first Neo4j Desktop Graph App in vanilla Javascript

Build your first Neo4j Desktop Graph App in vanilla Javascript

25 Jul 2019 by Aldrin Misquitta · 6 min read Neo4j Web Apps Beginner Graph Apps

Neo4j Desktop, part of the Neo4j Graph Platform, is a client application that installs on your desktop OS. It lets you get started quickly by downloading and installing the enterprise edition, and supported plugins. You can group related graphs and applications under a Project. You can also build single-page web applications that run within Neo4j Desktop and have access to these services provided by Neo4j Desktop. There are a number of apps available at https://install.graphapp.io/

Avoid cycles in Cypher queries

Avoid cycles in Cypher queries

26 Apr 2019 by Jan Zak · 3 min read Neo4j Beginner Cypher

There is one common performance issue our clients run into when trying their first Cypher queries on a dataset in Neo4j. When writing a query, be sure that it doesn’t match any cycles, or you can experience unpleasant surprises.

Lean Dependencies- Reduce Project Delivery Chaos with Graphs

Lean Dependencies- Reduce Project Delivery Chaos with Graphs

20 Feb 2019 by Luanne Misquitta · 6 min read Neo4j Beginner

Dependencies, like graphs, are everywhere. Achieving a goal is rarely possible in a vacuum and requires collaboration between individuals and/or processes.Eliminating dependencies completely is unrealistic- they are a part of life- but they can be streamlined to improve efficiency and reduce friction.

(Un)common Use Cases for Graph Databases

18 Apr 2016 by Michal Bachman · 3 min read Neo4j Beginner Modelling

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

Neo4j Events (Spring/Summer 2015)

27 Mar 2015 by Michal Bachman · 1 min read Neo4j Events Beginner

At GraphAware, we are very excited about the recently released Neo4j 2.2 and would like to share some info about whereyou can meet us in the next few weeks and months. Come and see us for a chat and learn something new about Neo4j and Graph Databases!

Announcing Spring Data Neo4j 4.0

24 Mar 2015 by Vince Bickers · 3 min read Neo4j Spring SDN Beginner

Over the last few months, GraphAware, Neo4j, and Pivotal engineers have been workingon a ground-up reimplementation of Spring Data Neo4j (SDN) that is server-first and Cypher-centric. Today we are veryexcited to announce the first milestone of the new Spring Data project for Neo4j.

Neo4j Events (Jan/Feb 2015)

16 Jan 2015 by Michal Bachman · 1 min read 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 organisedby GraphAware around the world in the next few weeks. We’ll be delighted to see you there!

Node Degrees in Neo4j 2.1

23 Jul 2014 by Michal Bachman · 3 min read Neo4j GraphAware Beginner

Efficient counting of relationships in Neo4j was the cornerstone of my Master Thesisand the reason the very first GraphAware Frameworkmodule called the Relationship Count Module was born. The improvements in Neo4j 2.1around dense nodes and the addition of getDegree(…) methods on the Node interface made me eager to do some benchmarking around relationship counts again.

Modelling Data in Neo4j: Bidirectional Relationships

11 Oct 2013 by Michal Bachman · 2 min read Neo4j Modelling Beginner

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