geekan · May 20, 2015 08:22 · May 20, 2015
diff --git a/cosine_similarity.scala b/cosine_similarity.scala
@@ -0,0 +1,65 @@
+/* 
+ * Object in scala for calculating cosine similarity
+ * Reuben Sutton - 2012
+ * More information: http://en.wikipedia.org/wiki/Cosine_similarity
+ */
+
+object CosineSimilarity {
+
+  /*
+   * This method takes 2 equal length arrays of integers 
+   * It returns a double representing similarity of the 2 arrays
+   * 0.9925 would be 99.25% similar
+   * (x dot y)/||X|| ||Y||
+   */
+  def cosineSimilarity(x: Array[Int], y: Array[Int]): Double = {
+    require(x.size == y.size)
+    dotProduct(x, y)/(magnitude(x) * magnitude(y))
+  }
+
+  /*
+   * Return the dot product of the 2 arrays
+   * e.g. (a[0]*b[0])+(a[1]*a[2])
+   */
+  def dotProduct(x: Array[Int], y: Array[Int]): Int = {
+    (for((a, b) <- x zip y) yield a * b) sum
+  }
+
+  /*
+   * Return the magnitude of an array
+   * We multiply each element, sum it, then square root the result.
+   */
+  def magnitude(x: Array[Int]): Double = {
+    math.sqrt(x map(i => i*i) sum)
+  }
+
+}
+
+ def similarity(t1: Map[String, Int], t2: Map[String, Int]): Double = {
+     //word, t1 freq, t2 freq
+     val m = scala.collection.mutable.HashMap[String, (Int, Int)]()
+
+     val sum1 = t1.foldLeft(0d) {case (sum, (word, freq)) =>
+         m += word ->(freq, 0)
+         sum + freq
+     }
+
+     val sum2 = t2.foldLeft(0d) {case (sum, (word, freq)) =>
+         m.get(word) match {
+             case Some((freq1, _)) => m += word ->(freq1, freq)
+             case None => m += word ->(0, freq)
+         }
+         sum + freq
+     }
+
+     val (p1, p2, p3) = m.foldLeft((0d, 0d, 0d)) {case ((s1, s2, s3), e) =>
+         val fs = e._2
+         val f1 = fs._1 / sum1
+         val f2 = fs._2 / sum2
+         (s1 + f1 * f2, s2 + f1 * f1, s3 + f2 * f2)
+     }
+
+     val cos = p1 / (Math.sqrt(p2) * Math.sqrt(p3))
+     cos
+ }
+