updated readme

README.md

@@ -1,11 +1,26 @@
-## communitize
+## SSimilarity
 
-### What this does
+### What this is 
 
-Runs a distributed computation of the cosine distance of the item-vecotrs of a user-item matrix
+Runs a distributed computation of the cosine distance of the item-vectors of a
+user-item matrix.  This value can be used as the basis for an item-based
+recommendation system.
+
+Benefits:
+
+* It's fully distributed
+* It handles string Ids (unlike Mahout)
+* It's short: only about 300 lines of scala code. 
+
+### Prereq
+
+* Hadoop 0.20.x
+* Apache Buildr
 
 ### How
 
+    bu clean package
+    rake clean default
 
 ### Input
 
@@ -47,15 +62,6 @@ Phase 3: Compute the pairwise cosine similarity for all item pairs that have bee
     where [1] is the sum of the product of the co-rated pref values (dot product) and 
           [2] is the product of the vector lengths 
 
-
-
-
-### Output
-
-Item-to-item similarity
-
-    xxx
-
 ### Credit
 
 * Outline originally based on ItemSimilarityJob in the Apache Mahout project. 

src/main/scala/SSimilarity.scala

@@ -203,7 +203,6 @@ object SSimilarity extends HadoopInterop {
           numerator += value 
           actualCoratedCount += 1
         }
-        println("min: %d act: %d", minimumCoratedCount, actualCoratedCount)
 
         if(actualCoratedCount >= minimumCoratedCount) { 
           var (idA, idB, length) = pair.parsedItemPairLength
@@ -245,8 +244,6 @@ object SSimilarity extends HadoopInterop {
   def truncate(d : Double, places : int) : Double = {
     return new java.math.BigDecimal(d, new java.math.MathContext(places)).doubleValue
   }
-
-
 
 }