OPENNLP-792 Added class javadoc. Thanks to Anthony Beylerian for providing a patch.
diff --git a/opennlp-wsd/src/main/java/opennlp/tools/disambiguator/oscc/OSCCME.java b/opennlp-wsd/src/main/java/opennlp/tools/disambiguator/oscc/OSCCME.java
index 1bb3410..7202680 100644
--- a/opennlp-wsd/src/main/java/opennlp/tools/disambiguator/oscc/OSCCME.java
+++ b/opennlp-wsd/src/main/java/opennlp/tools/disambiguator/oscc/OSCCME.java
@@ -36,6 +36,28 @@
import opennlp.tools.util.ObjectStreamUtils;
import opennlp.tools.util.TrainingParameters;
+/**
+ * Maximum Entropy version of the <b>one sence per cluster</b> approach in
+ *
+ * http://nlp.cs.rpi.edu/paper/wsd.pdf
+ *
+ * The approach is a hybrid approach using unsupervised context clustering to
+ * enhance disambiguation using a typical classifier.
+ *
+ * The context clusters are considered a group of words representing an enriched
+ * context of a target word.
+ *
+ * The clusters can be formed by clustering techniques like K-means, or a
+ * simpler version can use WordNet to get clusters simply from SynSets.
+ *
+ * Please see {@link DefaultOSCCContextGenerator}
+ *
+ * The approach finds the context clusters surrounding the target and uses a
+ * classifier to judge on the best case.
+ *
+ * Here an ME classifier is used.
+ *
+*/
public class OSCCME extends WSDisambiguator {
protected OSCCModel osccModel;
