Index: chrome/browser/history/scored_history_match.cc |
diff --git a/chrome/browser/history/scored_history_match.cc b/chrome/browser/history/scored_history_match.cc |
index e713b2575df6caf2d206ec399eb901b3bd96db01..53565e734fb83c44a9e1aa1a92e4f1f051d3cc63 100644 |
--- a/chrome/browser/history/scored_history_match.cc |
+++ b/chrome/browser/history/scored_history_match.cc |
@@ -152,9 +152,9 @@ ScoredHistoryMatch::ScoredHistoryMatch( |
const float topicality_score = GetTopicalityScore( |
terms.size(), url, terms_to_word_starts_offsets, word_starts); |
- const float frecency_score = GetFrecency( |
+ const float frequency_score = GetFrequency( |
now, (bookmark_service && bookmark_service->IsBookmarked(gurl)), visits); |
- raw_score_ = GetFinalRelevancyScore(topicality_score, frecency_score); |
+ raw_score_ = GetFinalRelevancyScore(topicality_score, frequency_score); |
raw_score_ = |
(raw_score_ <= kint32max) ? static_cast<int>(raw_score_) : kint32max; |
@@ -519,9 +519,9 @@ void ScoredHistoryMatch::FillInDaysAgoToRecencyScoreArray() { |
} |
// static |
-float ScoredHistoryMatch::GetFrecency(const base::Time& now, |
- const bool bookmarked, |
- const VisitInfoVector& visits) { |
+float ScoredHistoryMatch::GetFrequency(const base::Time& now, |
+ const bool bookmarked, |
+ const VisitInfoVector& visits) { |
// Compute the weighted average |value_of_transition| over the last at |
// most kMaxVisitsToScore visits, where each visit is weighted using |
// GetRecencyScore() based on how many days ago it happened. Use |
@@ -543,14 +543,14 @@ float ScoredHistoryMatch::GetFrecency(const base::Time& now, |
// static |
float ScoredHistoryMatch::GetFinalRelevancyScore(float topicality_score, |
- float frecency_score) { |
+ float frequency_score) { |
if (topicality_score == 0) |
return 0; |
// Here's how to interpret intermediate_score: Suppose the omnibox |
// has one input term. Suppose we have a URL for which the omnibox |
// input term has a single URL hostname hit at a word boundary. (This |
// implies topicality_score = 1.0.). Then the intermediate_score for |
- // this URL will depend entirely on the frecency_score with |
+ // this URL will depend entirely on the frequency_score with |
// this interpretation: |
// - a single typed visit more than three months ago, no other visits -> 0.2 |
// - a visit every three days, no typed visits -> 0.706 |
@@ -559,7 +559,7 @@ float ScoredHistoryMatch::GetFinalRelevancyScore(float topicality_score, |
// - a typed visit once a week -> 11.77 |
// - a typed visit every three days -> 14.12 |
// - at least ten typed visits today -> 20.0 (maximum score) |
- const float intermediate_score = topicality_score * frecency_score; |
+ const float intermediate_score = topicality_score * frequency_score; |
// The below code maps intermediate_score to the range [0, 1399]. |
// The score maxes out at 1400 (i.e., cannot beat a good inline result). |
if (intermediate_score <= 1) { |