From 1a9ea85f683c892592d7092c361e835c8b0f4f3e Mon Sep 17 00:00:00 2001
From: Stephen Blott
Date: Tue, 5 May 2015 06:14:12 +0100
Subject: Search completion; tweak scoring.

---
 background_scripts/completion.coffee | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

(limited to 'background_scripts')

diff --git a/background_scripts/completion.coffee b/background_scripts/completion.coffee
index e76139c2..33d8a563 100644
--- a/background_scripts/completion.coffee
+++ b/background_scripts/completion.coffee
@@ -353,6 +353,8 @@ class SearchEngineCompleter
       suggestions.push @mkSuggestion null, queryTerms, type, mkUrl(query), title, @computeRelevancy, 1
       suggestions[0].autoSelect = true
       queryTerms = queryTerms[1..]
+    else
+      query = queryTerms.join " "
 
     if queryTerms.length == 0
       return onComplete suggestions
@@ -367,13 +369,11 @@ class SearchEngineCompleter
       #     relevancy).  We assume that the completion engine has already factored that in.  Also, completion
       #     engines often handle spelling mistakes, in which case we wouldn't find the query terms in the
       #     suggestion anyway.
-      #   - The score is based on the length of the last query term.  The idea is that the user is already
-      #     happy with the earlier terms.
-      #   - The score is higher if the last query term is longer.  The idea is that search suggestions are more
+      #   - The score is higher if the query term is longer.  The idea is that search suggestions are more
       #     likely to be relevant if, after typing some number of characters, the user hasn't yet found
       #     a useful suggestion from another completer.
       #   - Scores are weighted such that they retain the order provided by the completion engine.
-      characterCount = queryTerms[queryTerms.length - 1].length
+      characterCount = query.length - queryTerms.length + 1
       score = 0.6 * (Math.min(characterCount, 10.0)/10.0)
 
       if 0 < existingSuggestions.length
-- 
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