Internet dating database
With graphs, it is possible to store big data sets and analyse it to provide user-centered insights.
Online dating is no longer seen as a last attempt for the desperate and lonely to find their soul mate.
Online dating websites have to sort through hundreds of thousands of users and preferences.
Thankfully, we are going to see that it’s easy to write a quick recommendation algorithm using Cypher, the query language for Neo4j.
With Neo4j, the algorithm can be expressed in a few lines of code and give results in real-time.
Current online dating site users explained their reasons for using online dating sites or apps with answers that included finding someone for a long term relationship or even marriage and the chance to meet people who just want to have fun.
It helps them suggest in real-time potential dates to their customers.
The better the suggestions, the more chances people will want to meet…and enjoy doing so.
As of April 2017, the leading dating website in the United States was with a U. As of the first quarter of 2017, the Match Group had 3.44 million paid subscribers across all its platforms in North America. Statista assumes no liability for the information given being complete or correct.
Dating apps are also a lucrative business - as of February 2017, some of the highest-grossing social apps in the Apple App Store worldwide were dating apps. Due to varying update cycles, statistics can display more up-to-date data than referenced in the text.It emulates the kind of data an online dating site would have. It has been prepared by Max de Marzi of Neo Technology who used to show how Neo4j can be used for match making.