Space: Apache Mahout (https://cwiki.apache.org/confluence/display/MAHOUT)
Page: RecommendationExamples
(https://cwiki.apache.org/confluence/display/MAHOUT/RecommendationExamples)
Edited by Sean Owen:
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h1. Introduction
This quick start page describes how to run the recommendation examples provided
by Mahout. Mahout comes with four recommendation mining examples. They are
based on netflixx, jester, grouplens and bookcrossing respectively.
h1. Steps
h2. Testing it on one single machine
In the examples directory type:
{code}
mvn -q exec:java
-Dexec.mainClass="org.apache.mahout.cf.taste.example.bookcrossing.BookCrossingRecommenderEvaluatorRunner"
-Dexec.args="<OPTIONS>"
mvn -q exec:java
-Dexec.mainClass="org.apache.mahout.cf.taste.example.netflix.NetflixRecommenderEvaluatorRunner"
-Dexec.args="<OPTIONS>"
mvn -q exec:java
-Dexec.mainClass="org.apache.mahout.cf.taste.example.netflix.TransposeToByUser"
-Dexec.args="<OPTIONS>"
mvn -q exec:java
-Dexec.mainClass="org.apache.mahout.cf.taste.example.jester.JesterRecommenderEvaluatorRunner"
-Dexec.args="<OPTIONS>"
mvn -q exec:java
-Dexec.mainClass="org.apache.mahout.cf.taste.example.grouplens.GroupLensRecommenderEvaluatorRunner"
-Dexec.args="<OPTIONS>"
{code}
Here, the command line options need only be:
{code}
-i [input file]
{code}
Note that the GroupLens example is designed for the "1 million" data set,
available at http://www.grouplens.org/node/73 . This file has an unusual format
and so has a special parser. The example code here can be easily modified to
use a regular FileDataModel and thus work on more standard input, including the
other data sets available at this site.
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