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 @@ Letâs 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>
