diff options
Diffstat (limited to 'background_scripts/completion.coffee')
| -rw-r--r-- | background_scripts/completion.coffee | 33 |
1 files changed, 18 insertions, 15 deletions
diff --git a/background_scripts/completion.coffee b/background_scripts/completion.coffee index cb5f64b0..5b5dc191 100644 --- a/background_scripts/completion.coffee +++ b/background_scripts/completion.coffee @@ -337,22 +337,32 @@ class SearchEngineCompleter type = if description? then description else "search" searchUrl = if custom then url else Settings.get "searchUrl" - query = queryTerms[1..].join " " + query = queryTerms[(if custom then 1 else 0)..].join " " # For custom search engines, we add an auto-selected suggestion. if custom title = if description? then query else queryTerms[0] + ": " + query - suggestions.push @mkSuggestion false, queryTerms, type, mkUrl(query), description, @computeRelevancy + suggestions.push @mkSuggestion false, queryTerms, type, mkUrl(query), description, @computeRelevancy, 1 suggestions[0].autoSelect = true - suggestions[0].relevancyScore = 1 queryTerms = queryTerms[1..] # For custom search-engine queries, this adds suggestions only if we have a completer. For other queries, # this adds suggestions for the default search engine (if we have a completer for that). - SearchEngines.complete searchUrl, queryTerms, (newSuggestions = []) => + SearchEngines.complete searchUrl, queryTerms, (searchSuggestions = []) => + + # Scoring: + # - The score does not depend upon the actual suggestion (so, it does not depend upon word relevancy). + # We assume that the completion engine has already factored that in. + # - The score is higher if the query is longer. The idea is that search suggestions are more likely + # to be relevant if, after typing quite some number of characters, the user hasn't yet found a + # useful suggestion from another completer. + # - Scores are weighted such that they retain the ordering provided by the completion engine. characterCount = query.length - queryTerms.length + 1 - for suggestion in newSuggestions - suggestions.push @mkSuggestion true, queryTerms, type, mkUrl(suggestion), suggestion, @computeRelevancy, characterCount + score = 0.8 * (Math.min(characterCount, 12.0)/12.0) + + for suggestion in searchSuggestions + suggestions.push @mkSuggestion true, queryTerms, type, mkUrl(suggestion), suggestion, @computeRelevancy, score + score *= 0.9 if custom for suggestion in suggestions @@ -365,15 +375,8 @@ class SearchEngineCompleter suggestion.insertText = insertText suggestion - computeRelevancy: (suggestion) -> - suggestion.relevancyScore ? - # We score search-engine completions by word relevancy, but weight the score increasingly as the number of - # characters in the query terms increases. The idea is that, the more the user has had to type, the less - # likely it is that one of the other suggestion types has proven useful, so the more likely it is that - # this suggestion will be useful. - # NOTE(smblott) This will require tweaking. - (Math.min(suggestion.extraRelevancyData, 12)/12) * - RankingUtils.wordRelevancy suggestion.queryTerms, suggestion.title, suggestion.title + # The score is computed in filter() and provided here via suggestion.extraRelevancyData. + computeRelevancy: (suggestion) -> suggestion.extraRelevancyData refresh: -> @searchEngines = SearchEngineCompleter.getSearchEngines() |