diff --git a/asterix-doc/src/site/markdown/AsterixSimilarityQueries.md b/asterix-doc/src/site/markdown/AsterixSimilarityQueries.md
index f9a7edd..3b07ca6 100644
--- a/asterix-doc/src/site/markdown/AsterixSimilarityQueries.md
+++ b/asterix-doc/src/site/markdown/AsterixSimilarityQueries.md
@@ -29,13 +29,13 @@
 `schwarzenegger` are `sch`, `chw`, `hwa`, ..., `ger`.
 
 AsterixDB provides
-[tokenization functions](AsterixDataTypesAndFunctions.html#Tokenizing_Functions)
+[tokenization functions](AsterixDBFunctions.html#Tokenizing_Functions)
 to convert strings to sets, and the
-[similarity functions](AsterixDataTypesAndFunctions.html#Similarity_Functions).
+[similarity functions](AsterixDBFunctions.html#Similarity_Functions).
 
 ## Similarity Selection Queries ## 
 
-The following [query](AsterixDataTypesAndFunctions.html#edit-distance)
+The following [query](AsterixDBFunctions.html#edit-distance)
 asks for all the Facebook users whose name is similar to
 `Suzanna Tilson`, i.e., their edit distance is at most 2.
 
@@ -47,7 +47,7 @@
         return $user
 
 
-The following [query](AsterixDataTypesAndFunctions.html#similarity-jaccard)
+The following [query](AsterixDBFunctions.html#similarity-jaccard)
 asks for all the Facebook users whose set of friend ids is
 similar to `[1,5,9]`, i.e., their Jaccard similarity is at least 0.6.
 
@@ -131,26 +131,43 @@
 The number "3" in "ngram(3)" is the length "n" in the grams. This
 index can be used to optimize similarity queries on this attribute
 using 
-[edit-distance](AsterixDataTypesAndFunctions.html#edit-distance), 
-[edit-distance-check](AsterixDataTypesAndFunctions.html#edit-distance-check), 
-or [Jaccard](AsterixDataTypesAndFunctions.html#similarity-jaccard) queries on this attribute where the
+[edit-distance](AsterixDBFunctions.html#edit-distance), 
+[edit-distance-check](AsterixDBFunctions.html#edit-distance-check), 
+or [Jaccard](AsterixDBFunctions.html#similarity-jaccard) queries on this attribute where the
 similarity is defined on sets of 3-grams.  This index can also be used
-to optimize queries with the "[contains()]((AsterixDataTypesAndFunctions.html#contains))" predicate (i.e., substring
+to optimize queries with the "[contains()]((AsterixDBFunctions.html#contains))" predicate (i.e., substring
 matching) since it can be also be solved by counting on the inverted
 list of the grams in the query string.
 
 ### Keyword Index ###
 
-A "keyword index" is also constructed on a set of strings.  Instead of 
-generating grams as in an ngram index, we generate tokens (e.g., words) from strings
-and for each token, construct an inverted list that includes the ids of the
-records with this token.  The follow example shows how to create a keyword index:
+A "keyword index" is constructed on a set of strings or sets (e.g., OrderedList, UnorderedList). Instead of 
+generating grams as in an ngram index, we generate tokens (e.g., words) and for each token, construct an inverted list that includes the ids of the
+records with this token.  The following two examples show how to create keyword index and query based on each data type:
+
+#### Keyword Index on String Type ####
 
         use dataverse TinySocial;
 
-        create index fbUserIdx on FacebookUsers(name) type keyword;
+        create index fbMessageIdx on FacebookMessages(message) type keyword;
 
-The keyword index can be used to optimize queries with token-based similarity predicates, including
-[similarity-jaccard](AsterixDataTypesAndFunctions.html#similarity-jaccard) and
-[similarity-jaccard-check](AsterixDataTypesAndFunctions.html#similarity-jaccard-check).
+        for $o in dataset('FacebookMessages')
+        let $jacc := similarity-jaccard-check(word-tokens($o.message), word-tokens("love like verizon"), 0.2f)
+        where $jacc[0]
+        return $o
+        
+#### Keyword Index on UnorderedList ####      
+        
+        use dataverse TinySocial;
+
+        create index fbUserIdx_fids on FacebookUsers(friend-ids) type keyword;
+
+        for $c in dataset('FacebookUsers')
+        let $jacc := similarity-jaccard-check($c.friend-ids, {{3,10}}, 0.5f)
+        where $jacc[0]
+        return $c
+        
+As shown above, the keyword index can be used to optimize queries with token-based similarity predicates, including
+[similarity-jaccard](AsterixDBFunctions.html#similarity-jaccard) and
+[similarity-jaccard-check](AsterixDBFunctions.html#similarity-jaccard-check).