svn commit: r1608637 - /mahout/site/mahout_cms/trunk/content/users/recommender/intro-als-hadoop.mdtext

[pa...@apache.org]

Author: pat
Date: Tue Jul  8 01:13:25 2014
New Revision: 1608637

URL: http://svn.apache.org/r1608637
Log:
Explain Mahout ID v application IDs

Modified:
    mahout/site/mahout_cms/trunk/content/users/recommender/intro-als-hadoop.mdtext

Modified: mahout/site/mahout_cms/trunk/content/users/recommender/intro-als-hadoop.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/mahout_cms/trunk/content/users/recommender/intro-als-hadoop.mdtext?rev=1608637&r1=1608636&r2=1608637&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/users/recommender/intro-als-hadoop.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/users/recommender/intro-als-hadoop.mdtext Tue Jul  8 01:13:25 2014
@@ -1,4 +1,3 @@
-
 # Introduction to ALS Recommendations with Hadoop
 
 ##Overview
@@ -52,7 +51,11 @@ Let’s look at a simple example of h
 
 **Step 1: Prepare test data**
 
-Similar to Mahout's item based recommender, the ALS recommender relies on the user to item preference data: *userID*, *itemID* and *preference*. The preference could be explicit numeric rating or counts of actions such as a click (implicit feedback). The test data file is organized as each line is a tab-delimited string, the 1st field is user id, which must be numeric, the 2nd field is item id, which must be numeric and the 3rd field is preference, which should also be a number.  
+Similar to Mahout's item based recommender, the ALS recommender relies on the user to item preference data: *userID*, *itemID* and *preference*. The preference could be explicit numeric rating or counts of actions such as a click (implicit feedback). The test data file is organized as each line is a tab-delimited string, the 1st field is user id, which must be numeric, the 2nd field is item id, which must be numeric and the 3rd field is preference, which should also be a number.
+
+**Note:** You must create IDs that are ordinal positive integers for all user and item IDs. Often this will require you to keep a dictionary
+to map into and out of Mahout IDs. For instance if the first user has ID "xyz" in your application, this would get an Mahout ID of the integer 1 and so on. The same
+for item IDs. Then after recommendations are calculated you will have to translate the Mahout user and item IDs back into your application IDs.
 
 To quickly start, you could specify a text file like following as the input:
 <pre>