An Inside Look at the Components of a Recommendation Engine

Recommendation engines help narrow your choices to those that best meet your particular needs.  In this post, we’re going to take a closer look at how all the different components of a recommendation engine work together. We’re going to use collaborative filtering on movie ratings data to recommend movies. The key components are a collaborative filtering algorithm in Apache Mahout to build and train a machine learning model, and search technology from Elasticsearch to simplify deployment of the recommender.

https://www.mapr.com/blog/inside-look-at-components-of-recommendati...

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Comment by Carol McDonald on April 15, 2015 at 1:42pm
Here is a tutorial which explains how to implement this https://www.mapr.com/products/mapr-sandbox-hadoop/tutorials/recomme...

Happy 10th year, JCertif!

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