March 2015
Intermediate to advanced
192 pages
4h 32m
English
Content preview from Neo4j High PerformanceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Building a recommendation system
Let us see how we can use Neo4j as the backbone to develop recommendation systems for different data scenarios. For this purpose, we will be using the collaborative filtering approach to process the data in hand and churn out relevant results.
In order to understand how the process works, let us use a simple data set of a dating site where you can sign in and view the profile of people who you could potentially date, and you can follow or like them, or vice versa. The graphical representation of such a dataset will represent the people as nodes, and the like operations from one person to another is represented as edges between them.
As shown in the following diagram, consider a user, John, who has just registered ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.