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authorStephen Blott2015-05-16 13:12:25 +0100
committerStephen Blott2015-05-16 13:12:25 +0100
commit87c214ffd80ac436273f35fd95c800589e3f7d4a (patch)
tree8dd72a7d4232c649ca1e721efbd35389df893d79 /background_scripts/completion.coffee
parent148f1b44bcbe7df030ac9f95498826ee66f0a9cd (diff)
downloadvimium-87c214ffd80ac436273f35fd95c800589e3f7d4a.tar.bz2
Search completion; tweak comments.
Diffstat (limited to 'background_scripts/completion.coffee')
-rw-r--r--background_scripts/completion.coffee12
1 files changed, 6 insertions, 6 deletions
diff --git a/background_scripts/completion.coffee b/background_scripts/completion.coffee
index 0675d13f..a8f160d0 100644
--- a/background_scripts/completion.coffee
+++ b/background_scripts/completion.coffee
@@ -155,8 +155,9 @@ class Suggestion
[ '.', [ "^https?://", "\\W+$" ].map (re) -> new RegExp re ]
]
- # Boost a score by a factor (in the range (0,1.0)), while keeping the score in the range [0,1]. This makes
- # greater adjustments to scores near the middle of the range (so, very poor relevancy scores remain poor).
+ # Boost a relevancy score by a factor (in the range (0,1.0)), while keeping the score in the range [0,1].
+ # This makes greater adjustments to scores near the middle of the range (so, very poor relevancy scores
+ # remain very poor).
@boostRelevancyScore: (factor, score) ->
score + if score < 0.5 then score * factor else (1.0 - score) * factor
@@ -453,9 +454,8 @@ class SearchEngineCompleter
factor = Math.max 0.0, Math.min 1.0, Settings.get "omniSearchWeight"
haveCompletionEngine = (0.0 < factor or custom) and CompletionSearch.haveCompletionEngine searchUrl
- # We weight the relevancy-score factor by the length of the query (exponentially). The idea is that, the
- # more the user has typed, the less likely it is that what the user is searching for is amonst the
- # suggestions from other completers.
+ # We weight the relevancy factor by the length of the query (exponentially). The idea is that, the
+ # more the user has typed, the less likely it is that another completer has proven fruitful.
factor *= 1 - Math.pow 0.8, query.length
# This filter is applied to all of the suggestions from all of the completers, after they have been
@@ -495,7 +495,7 @@ class SearchEngineCompleter
isCustomSearch: custom
relevancyFunction: @computeRelevancy
# We reduce the relevancy factor as suggestions are added. This respects, to some extent, the
- # suggestion order provided by the completion engine.
+ # order provided by the completion engine.
relevancyData: factor *= 0.95
cachedSuggestions =