Add ERR to ranking evaluation documentation

This change adds a section about the Expected Reciprocal Rank metric (ERR) to
the Ranking Evaluation documentation.

Author: Christoph Büscher

docs/reference/search/rank-eval.asciidoc

@@ -259,6 +259,56 @@ in the query. Defaults to 10.
 |`normalize` | If set to `true`, this metric will calculate the https://en.wikipedia.org/wiki/Discounted_cumulative_gain#Normalized_DCG[Normalized DCG].
 |=======================================================================
 
+[float]
+==== Expected Reciprocal Rank (ERR)
+
+Expected Reciprocal Rank (ERR) is an extension of the classical reciprocal rank for the graded relevance case
+(Chapelle, Olivier, Donald Metzler, Ya Zhang, and Pierre Grinspan. 2009. 
+http://olivier.chapelle.cc/pub/err.pdf[Expected reciprocal rank for graded relevance].)
+
+It is based on the assumption of a cascade model of search, which models that a user scans through ranked search 
+results in order and stops at the first document satisfies the information need of the user. For this reason, it
+is a good metric for question answering and navigation queries, but less for survey oriented information needs
+where the user is interested in finding several relevant documents in the top k results.
+
+The metric tries to model the expectation of the reciprocal of the position of a result at which a user stops.
+This means, relevant document in top ranking positions will contribute much to the overall ERR score. The same 
+document will contribute much less to the score on a lower rank, but even more so if there were some
+relevant documents preceding it. By this, ERR discounts documents which are shown below very relevant documents
+and introduces some kind of dependency in the ordering of relevant documents.
+
+[source,js]
+--------------------------------
+GET /twitter/_rank_eval
+{
+    "requests": [
+    {
+        "id": "JFK query", 
+        "request": { "query": { "match_all": {}}},
+        "ratings": []  
+    }],
+    "metric": {
+       "expected_reciprocal_rank": {
+            "maximum_relevance" : 3,
+            "k" : 20
+       }
+    }
+}
+--------------------------------
+// CONSOLE
+// TEST[setup:twitter]
+
+The `expected_reciprocal_rank` metric takes the following parameters:
+
+[cols="<,<",options="header",]
+|=======================================================================
+|Parameter |Description
+| `maximum_relevance` | Mandatory parameter. The highest relevance grade used in the user supplied
+relevance judgments.
+|`k` | sets the maximum number of documents retrieved per query. This value will act in place of the usual `size` parameter
+in the query. Defaults to 10.
+|=======================================================================
+
 [float]
 === Response format