Author: srowen
Date: Wed Mar 10 13:51:28 2010
New Revision: 921351
URL: http://svn.apache.org/viewvc?rev=921351&view=rev
Log:
Update examples to use a little more data for more consistent results
Modified:
lucene/mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/example/bookcrossing/BookCrossingRecommender.java
Modified:
lucene/mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/example/bookcrossing/BookCrossingRecommender.java
URL:
http://svn.apache.org/viewvc/lucene/mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/example/bookcrossing/BookCrossingRecommender.java?rev=921351&r1=921350&r2=921351&view=diff
==============================================================================
---
lucene/mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/example/bookcrossing/BookCrossingRecommender.java
(original)
+++
lucene/mahout/trunk/examples/src/main/java/org/apache/mahout/cf/taste/example/bookcrossing/BookCrossingRecommender.java
Wed Mar 10 13:51:28 2010
@@ -26,7 +26,7 @@ import org.apache.mahout.cf.taste.impl.n
import org.apache.mahout.cf.taste.impl.recommender.CachingRecommender;
import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender;
import org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity;
-import org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity;
+import org.apache.mahout.cf.taste.impl.similarity.EuclideanDistanceSimilarity;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
import org.apache.mahout.cf.taste.recommender.IDRescorer;
@@ -39,12 +39,12 @@ import org.apache.mahout.cf.taste.simila
* See the <a href="http://www.informatik.uni-freiburg.de/~cziegler/BX/";>Book
Crossing site</a>.
*/
public final class BookCrossingRecommender implements Recommender {
-
+
private final Recommender recommender;
-
+
public BookCrossingRecommender(DataModel bcModel) throws TasteException {
- UserSimilarity similarity = new CachingUserSimilarity(new
PearsonCorrelationSimilarity(bcModel), bcModel);
- UserNeighborhood neighborhood = new NearestNUserNeighborhood(10, 0.0,
similarity, bcModel, 0.25);
+ UserSimilarity similarity = new CachingUserSimilarity(new
EuclideanDistanceSimilarity(bcModel), bcModel);
+ UserNeighborhood neighborhood = new NearestNUserNeighborhood(10, 0.2,
similarity, bcModel, 0.2);
recommender = new CachingRecommender(new
GenericUserBasedRecommender(bcModel, neighborhood, similarity));
}
