Index: chrome/browser/autocomplete/scored_history_match_builder_impl.cc |
diff --git a/chrome/browser/autocomplete/scored_history_match_builder_impl.cc b/chrome/browser/autocomplete/scored_history_match_builder_impl.cc |
deleted file mode 100644 |
index b5b8676e994c84e2d111206f6e8ac470bd6955ae..0000000000000000000000000000000000000000 |
--- a/chrome/browser/autocomplete/scored_history_match_builder_impl.cc |
+++ /dev/null |
@@ -1,689 +0,0 @@ |
-// Copyright (c) 2012 The Chromium Authors. All rights reserved. |
-// Use of this source code is governed by a BSD-style license that can be |
-// found in the LICENSE file. |
- |
-#include "chrome/browser/autocomplete/scored_history_match_builder_impl.h" |
- |
-#include <math.h> |
- |
-#include <algorithm> |
-#include <vector> |
- |
-#include "base/logging.h" |
-#include "base/metrics/histogram.h" |
-#include "base/numerics/safe_conversions.h" |
-#include "base/strings/string_number_conversions.h" |
-#include "base/strings/string_split.h" |
-#include "base/strings/string_util.h" |
-#include "base/strings/utf_string_conversions.h" |
-#include "chrome/browser/autocomplete/history_url_provider.h" |
-#include "components/bookmarks/browser/bookmark_model.h" |
-#include "components/bookmarks/browser/bookmark_utils.h" |
-#include "components/history/core/browser/history_client.h" |
-#include "components/omnibox/omnibox_field_trial.h" |
-#include "components/omnibox/url_prefix.h" |
-#include "content/public/browser/browser_thread.h" |
- |
-namespace { |
- |
-// The number of days of recency scores to precompute. |
-const int kDaysToPrecomputeRecencyScoresFor = 366; |
- |
-// The number of raw term score buckets use; raw term scores greater this are |
-// capped at the score of the largest bucket. |
-const int kMaxRawTermScore = 30; |
- |
-// If true, assign raw scores to be max(whatever it normally would be, a score |
-// that's similar to the score HistoryURL provider would assign). This variable |
-// is set in the constructor by examining the field trial state. |
-const bool kAlsoDoHupLikeScoring = false; |
- |
-// Pre-computed information to speed up calculating recency scores. |
-// |days_ago_to_recency_score| is a simple array mapping how long ago a page was |
-// visited (in days) to the recency score we should assign it. This allows easy |
-// lookups of scores without requiring math. This is initialized by |
-// InitDaysAgoToRecencyScoreArray called by |
-// ScoredHistoryMatchBuilderImpl::Init(). |
-float days_ago_to_recency_score[kDaysToPrecomputeRecencyScoresFor]; |
- |
-// Pre-computed information to speed up calculating topicality scores. |
-// |raw_term_score_to_topicality_score| is a simple array mapping how raw terms |
-// scores (a weighted sum of the number of hits for the term, weighted by how |
-// important the hit is: hostname, path, etc.) to the topicality score we should |
-// assign it. This allows easy lookups of scores without requiring math. This |
-// is initialized by InitRawTermScoreToTopicalityScoreArray() called from |
-// ScoredHistoryMatchBuilderImpl::Init(). |
-float raw_term_score_to_topicality_score[kMaxRawTermScore]; |
- |
-// The maximum score that can be assigned to non-inlineable matches. This is |
-// useful because often we want inlineable matches to come first (even if they |
-// don't sometimes score as well as non-inlineable matches) because if a |
-// non-inlineable match comes first than all matches will get demoted later in |
-// HistoryQuickProvider to non-inlineable scores. Set to -1 to indicate no |
-// maximum score. |
-int max_assigned_score_for_non_inlineable_matches = -1; |
- |
-// Whether ScoredHistoryMatchBuilderImpl::Init() has been called. |
-bool initialized = false; |
- |
-// Precalculates raw_term_score_to_topicality_score, used in |
-// GetTopicalityScore(). |
-void InitRawTermScoreToTopicalityScoreArray() { |
- for (int term_score = 0; term_score < kMaxRawTermScore; ++term_score) { |
- float topicality_score; |
- if (term_score < 10) { |
- // If the term scores less than 10 points (no full-credit hit, or |
- // no combination of hits that score that well), then the topicality |
- // score is linear in the term score. |
- topicality_score = 0.1 * term_score; |
- } else { |
- // For term scores of at least ten points, pass them through a log |
- // function so a score of 10 points gets a 1.0 (to meet up exactly |
- // with the linear component) and increases logarithmically until |
- // maxing out at 30 points, with computes to a score around 2.1. |
- topicality_score = (1.0 + 2.25 * log10(0.1 * term_score)); |
- } |
- raw_term_score_to_topicality_score[term_score] = topicality_score; |
- } |
-} |
- |
-// Pre-calculates days_ago_to_recency_score, used in GetRecencyScore(). |
-void InitDaysAgoToRecencyScoreArray() { |
- for (int days_ago = 0; days_ago < kDaysToPrecomputeRecencyScoresFor; |
- days_ago++) { |
- int unnormalized_recency_score; |
- if (days_ago <= 4) { |
- unnormalized_recency_score = 100; |
- } else if (days_ago <= 14) { |
- // Linearly extrapolate between 4 and 14 days so 14 days has a score |
- // of 70. |
- unnormalized_recency_score = 70 + (14 - days_ago) * (100 - 70) / (14 - 4); |
- } else if (days_ago <= 31) { |
- // Linearly extrapolate between 14 and 31 days so 31 days has a score |
- // of 50. |
- unnormalized_recency_score = 50 + (31 - days_ago) * (70 - 50) / (31 - 14); |
- } else if (days_ago <= 90) { |
- // Linearly extrapolate between 30 and 90 days so 90 days has a score |
- // of 30. |
- unnormalized_recency_score = 30 + (90 - days_ago) * (50 - 30) / (90 - 30); |
- } else { |
- // Linearly extrapolate between 90 and 365 days so 365 days has a score |
- // of 10. |
- unnormalized_recency_score = |
- 10 + (365 - days_ago) * (20 - 10) / (365 - 90); |
- } |
- days_ago_to_recency_score[days_ago] = unnormalized_recency_score / 100.0; |
- if (days_ago > 0) { |
- DCHECK_LE(days_ago_to_recency_score[days_ago], |
- days_ago_to_recency_score[days_ago - 1]); |
- } |
- } |
-} |
- |
-} // namespace |
- |
-// static |
-int ScoredHistoryMatchBuilderImpl::bookmark_value_ = 1; |
-bool ScoredHistoryMatchBuilderImpl::allow_tld_matches_ = false; |
-bool ScoredHistoryMatchBuilderImpl::allow_scheme_matches_ = false; |
-bool ScoredHistoryMatchBuilderImpl::hqp_experimental_scoring_enabled_ = false; |
-float ScoredHistoryMatchBuilderImpl::topicality_threshold_ = -1; |
-std::vector<ScoredHistoryMatchBuilderImpl::ScoreMaxRelevance>* |
- ScoredHistoryMatchBuilderImpl::hqp_relevance_buckets_ = NULL; |
- |
-ScoredHistoryMatchBuilderImpl::ScoredHistoryMatchBuilderImpl( |
- const IsBookmarkedCallback& is_bookmarked) |
- : is_bookmarked_(is_bookmarked) { |
- Init(); |
-} |
- |
-ScoredHistoryMatchBuilderImpl::~ScoredHistoryMatchBuilderImpl() { |
-} |
- |
-ScoredHistoryMatch ScoredHistoryMatchBuilderImpl::Build( |
- const history::URLRow& row, |
- const VisitInfoVector& visits, |
- const std::string& languages, |
- const base::string16& lower_string, |
- const String16Vector& terms, |
- const WordStarts& terms_to_word_starts_offsets, |
- const RowWordStarts& word_starts, |
- const base::Time now) const { |
- ScoredHistoryMatch scored_history_match = ScoredHistoryMatch( |
- row, 0, false, false, 0, TermMatches(), TermMatches(), false); |
- |
- GURL gurl = row.url(); |
- if (!gurl.is_valid()) |
- return scored_history_match; |
- |
- // Figure out where each search term appears in the URL and/or page title |
- // so that we can score as well as provide autocomplete highlighting. |
- base::OffsetAdjuster::Adjustments adjustments; |
- base::string16 url = |
- bookmarks::CleanUpUrlForMatching(gurl, languages, &adjustments); |
- base::string16 title = bookmarks::CleanUpTitleForMatching(row.title()); |
- int term_num = 0; |
- for (const auto& term : terms) { |
- TermMatches url_term_matches = MatchTermInString(term, url, term_num); |
- TermMatches title_term_matches = MatchTermInString(term, title, term_num); |
- if (url_term_matches.empty() && title_term_matches.empty()) { |
- // A term was not found in either URL or title - reject. |
- return scored_history_match; |
- } |
- scored_history_match.url_matches.insert( |
- scored_history_match.url_matches.end(), url_term_matches.begin(), |
- url_term_matches.end()); |
- scored_history_match.title_matches.insert( |
- scored_history_match.title_matches.end(), title_term_matches.begin(), |
- title_term_matches.end()); |
- ++term_num; |
- } |
- |
- // Sort matches by offset and eliminate any which overlap. |
- // TODO(mpearson): Investigate whether this has any meaningful |
- // effect on scoring. (It's necessary at some point: removing |
- // overlaps and sorting is needed to decide what to highlight in the |
- // suggestion string. But this sort and de-overlap doesn't have to |
- // be done before scoring.) |
- scored_history_match.url_matches = |
- SortAndDeoverlapMatches(scored_history_match.url_matches); |
- scored_history_match.title_matches = |
- SortAndDeoverlapMatches(scored_history_match.title_matches); |
- |
- // We can inline autocomplete a match if: |
- // 1) there is only one search term |
- // 2) AND the match begins immediately after one of the prefixes in |
- // URLPrefix such as http://www and https:// (note that one of these |
- // is the empty prefix, for cases where the user has typed the scheme) |
- // 3) AND the search string does not end in whitespace (making it look to |
- // the IMUI as though there is a single search term when actually there |
- // is a second, empty term). |
- // |best_inlineable_prefix| stores the inlineable prefix computed in |
- // clause (2) or NULL if no such prefix exists. (The URL is not inlineable.) |
- // Note that using the best prefix here means that when multiple |
- // prefixes match, we'll choose to inline following the longest one. |
- // For a URL like "http://www.washingtonmutual.com", this means |
- // typing "w" will inline "ashington..." instead of "ww.washington...". |
- if (!scored_history_match.url_matches.empty() && (terms.size() == 1) && |
- !IsWhitespace(*lower_string.rbegin())) { |
- const base::string16 gurl_spec = base::UTF8ToUTF16(gurl.spec()); |
- const URLPrefix* best_inlineable_prefix = |
- URLPrefix::BestURLPrefix(gurl_spec, terms[0]); |
- if (best_inlineable_prefix) { |
- // Initialize innermost_match. |
- // The idea here is that matches that occur in the scheme or |
- // "www." are worse than matches which don't. For the URLs |
- // "http://www.google.com" and "http://wellsfargo.com", we want |
- // the omnibox input "w" to cause the latter URL to rank higher |
- // than the former. Note that this is not the same as checking |
- // whether one match's inlinable prefix has more components than |
- // the other match's, since in this example, both matches would |
- // have an inlinable prefix of "http://", which is one component. |
- // |
- // Instead, we look for the overall best (i.e., most components) |
- // prefix of the current URL, and then check whether the inlinable |
- // prefix has that many components. If it does, this is an |
- // "innermost" match, and should be boosted. In the example |
- // above, the best prefixes for the two URLs have two and one |
- // components respectively, while the inlinable prefixes each |
- // have one component; this means the first match is not innermost |
- // and the second match is innermost, resulting in us boosting the |
- // second match. |
- // |
- // Now, the code that implements this. |
- // The deepest prefix for this URL regardless of where the match is. |
- const URLPrefix* best_prefix = |
- URLPrefix::BestURLPrefix(gurl_spec, base::string16()); |
- DCHECK(best_prefix); |
- // If the URL is inlineable, we must have a match. Note the prefix that |
- // makes it inlineable may be empty. |
- scored_history_match.can_inline = true; |
- scored_history_match.innermost_match = |
- best_inlineable_prefix->num_components == best_prefix->num_components; |
- } |
- } |
- |
- const float topicality_score = |
- GetTopicalityScore(terms.size(), url, terms_to_word_starts_offsets, |
- word_starts, &scored_history_match); |
- const float frequency_score = GetFrequency( |
- now, (!is_bookmarked_.is_null() && is_bookmarked_.Run(gurl)), visits); |
- scored_history_match.raw_score = base::saturated_cast<int>( |
- GetFinalRelevancyScore(topicality_score, frequency_score, |
- *hqp_relevance_buckets_)); |
- |
- if (kAlsoDoHupLikeScoring && scored_history_match.can_inline) { |
- // HistoryURL-provider-like scoring gives any match that is |
- // capable of being inlined a certain minimum score. Some of these |
- // are given a higher score that lets them be shown in inline. |
- // This test here derives from the test in |
- // HistoryURLProvider::PromoteMatchForInlineAutocomplete(). |
- const bool promote_to_inline = |
- (row.typed_count() > 1) || |
- (scored_history_match.IsHostOnly() && (row.typed_count() == 1)); |
- int hup_like_score = promote_to_inline ? |
- HistoryURLProvider::kScoreForBestInlineableResult : |
- HistoryURLProvider::kBaseScoreForNonInlineableResult; |
- |
- // Also, if the user types the hostname of a host with a typed |
- // visit, then everything from that host get given inlineable scores |
- // (because the URL-that-you-typed will go first and everything |
- // else will be assigned one minus the previous score, as coded |
- // at the end of HistoryURLProvider::DoAutocomplete(). |
- if (base::UTF8ToUTF16(gurl.host()) == terms[0]) |
- hup_like_score = HistoryURLProvider::kScoreForBestInlineableResult; |
- |
- // HistoryURLProvider has the function PromoteOrCreateShorterSuggestion() |
- // that's meant to promote prefixes of the best match (if they've |
- // been visited enough related to the best match) or |
- // create/promote host-only suggestions (even if they've never |
- // been typed). The code is complicated and we don't try to |
- // duplicate the logic here. Instead, we handle a simple case: in |
- // low-typed-count ranges, give host-only matches (i.e., |
- // http://www.foo.com/ vs. http://www.foo.com/bar.html) a boost so |
- // that the host-only match outscores all the other matches that |
- // would normally have the same base score. This behavior is not |
- // identical to what happens in HistoryURLProvider even in these |
- // low typed count ranges--sometimes it will create/promote when |
- // this test does not (indeed, we cannot create matches like HUP |
- // can) and vice versa--but the underlying philosophy is similar. |
- if (!promote_to_inline && scored_history_match.IsHostOnly()) |
- hup_like_score++; |
- |
- // All the other logic to goes into hup-like-scoring happens in |
- // the tie-breaker case of MatchScoreGreater(). |
- |
- // Incorporate hup_like_score into raw_score. |
- scored_history_match.raw_score = |
- std::max(scored_history_match.raw_score, hup_like_score); |
- } |
- |
- // If this match is not inlineable and there's a cap on the maximum |
- // score that can be given to non-inlineable matches, apply the cap. |
- if (!scored_history_match.can_inline && |
- (max_assigned_score_for_non_inlineable_matches != -1)) { |
- scored_history_match.raw_score = |
- std::min(scored_history_match.raw_score, |
- max_assigned_score_for_non_inlineable_matches); |
- } |
- |
- // Now that we're done processing this entry, correct the offsets of the |
- // matches in |url_matches| so they point to offsets in the original URL |
- // spec, not the cleaned-up URL string that we used for matching. |
- std::vector<size_t> offsets = |
- OffsetsFromTermMatches(scored_history_match.url_matches); |
- base::OffsetAdjuster::UnadjustOffsets(adjustments, &offsets); |
- scored_history_match.url_matches = |
- ReplaceOffsetsInTermMatches(scored_history_match.url_matches, offsets); |
- |
- return scored_history_match; |
-} |
- |
-// static |
-TermMatches ScoredHistoryMatchBuilderImpl::FilterTermMatchesByWordStarts( |
- const TermMatches& term_matches, |
- const WordStarts& terms_to_word_starts_offsets, |
- const WordStarts& word_starts, |
- size_t start_pos, |
- size_t end_pos) { |
- // Return early if no filtering is needed. |
- if (start_pos == std::string::npos) |
- return term_matches; |
- TermMatches filtered_matches; |
- WordStarts::const_iterator next_word_starts = word_starts.begin(); |
- WordStarts::const_iterator end_word_starts = word_starts.end(); |
- for (const auto& term_match : term_matches) { |
- const size_t term_offset = |
- terms_to_word_starts_offsets[term_match.term_num]; |
- // Advance next_word_starts until it's >= the position of the term we're |
- // considering (adjusted for where the word begins within the term). |
- while ((next_word_starts != end_word_starts) && |
- (*next_word_starts < (term_match.offset + term_offset))) |
- ++next_word_starts; |
- // Add the match if it's before the position we start filtering at or |
- // after the position we stop filtering at (assuming we have a position |
- // to stop filtering at) or if it's at a word boundary. |
- if ((term_match.offset < start_pos) || |
- ((end_pos != std::string::npos) && (term_match.offset >= end_pos)) || |
- ((next_word_starts != end_word_starts) && |
- (*next_word_starts == term_match.offset + term_offset))) |
- filtered_matches.push_back(term_match); |
- } |
- return filtered_matches; |
-} |
- |
-void ScoredHistoryMatchBuilderImpl::Init() { |
- // Because the code below is not thread safe, we check that we're only calling |
- // it from one thread: the UI thread. Specifically, we check "if we've heard |
- // of the UI thread then we'd better be on it." The first part is necessary |
- // so unit tests pass. (Many unit tests don't set up the threading naming |
- // system; hence CurrentlyOn(UI thread) will fail.) |
- using content::BrowserThread; |
- DCHECK(!BrowserThread::IsThreadInitialized(BrowserThread::UI) || |
- BrowserThread::CurrentlyOn(BrowserThread::UI)); |
- |
- if (initialized) |
- return; |
- |
- initialized = true; |
- |
- // When doing HUP-like scoring, don't allow a non-inlineable match |
- // to beat the score of good inlineable matches. This is a problem |
- // because if a non-inlineable match ends up with the highest score |
- // from HistoryQuick provider, all HistoryQuick matches get demoted |
- // to non-inlineable scores (scores less than 1200). Without |
- // HUP-like-scoring, these results would actually come from the HUP |
- // and not be demoted, thus outscoring the demoted HQP results. |
- // When the HQP provides these, we need to clamp the non-inlineable |
- // results to preserve this behavior. |
- if (kAlsoDoHupLikeScoring) { |
- max_assigned_score_for_non_inlineable_matches = |
- HistoryURLProvider::kScoreForBestInlineableResult - 1; |
- } |
- bookmark_value_ = OmniboxFieldTrial::HQPBookmarkValue(); |
- allow_tld_matches_ = OmniboxFieldTrial::HQPAllowMatchInTLDValue(); |
- allow_scheme_matches_ = OmniboxFieldTrial::HQPAllowMatchInSchemeValue(); |
- |
- InitRawTermScoreToTopicalityScoreArray(); |
- InitDaysAgoToRecencyScoreArray(); |
- InitHQPExperimentalParams(); |
-} |
- |
-// static |
-float ScoredHistoryMatchBuilderImpl::GetTopicalityScore( |
- const int num_terms, |
- const base::string16& url, |
- const WordStarts& terms_to_word_starts_offsets, |
- const RowWordStarts& word_starts, |
- ScoredHistoryMatch* scored_history_match) { |
- DCHECK(initialized); |
- // A vector that accumulates per-term scores. The strongest match--a |
- // match in the hostname at a word boundary--is worth 10 points. |
- // Everything else is less. In general, a match that's not at a word |
- // boundary is worth about 1/4th or 1/5th of a match at the word boundary |
- // in the same part of the URL/title. |
- DCHECK_GT(num_terms, 0); |
- std::vector<int> term_scores(num_terms, 0); |
- WordStarts::const_iterator next_word_starts = |
- word_starts.url_word_starts_.begin(); |
- WordStarts::const_iterator end_word_starts = |
- word_starts.url_word_starts_.end(); |
- const size_t question_mark_pos = url.find('?'); |
- const size_t colon_pos = url.find(':'); |
- // The + 3 skips the // that probably appears in the protocol |
- // after the colon. If the protocol doesn't have two slashes after |
- // the colon, that's okay--all this ends up doing is starting our |
- // search for the next / a few characters into the hostname. The |
- // only times this can cause problems is if we have a protocol without |
- // a // after the colon and the hostname is only one or two characters. |
- // This isn't worth worrying about. |
- const size_t end_of_hostname_pos = (colon_pos != std::string::npos) ? |
- url.find('/', colon_pos + 3) : url.find('/'); |
- size_t last_part_of_hostname_pos = |
- (end_of_hostname_pos != std::string::npos) ? |
- url.rfind('.', end_of_hostname_pos) : url.rfind('.'); |
- // Loop through all URL matches and score them appropriately. |
- // First, filter all matches not at a word boundary and in the path (or |
- // later). |
- scored_history_match->url_matches = FilterTermMatchesByWordStarts( |
- scored_history_match->url_matches, terms_to_word_starts_offsets, |
- word_starts.url_word_starts_, end_of_hostname_pos, std::string::npos); |
- if (colon_pos != std::string::npos) { |
- // Also filter matches not at a word boundary and in the scheme. |
- scored_history_match->url_matches = FilterTermMatchesByWordStarts( |
- scored_history_match->url_matches, terms_to_word_starts_offsets, |
- word_starts.url_word_starts_, 0, colon_pos); |
- } |
- for (const auto& url_match : scored_history_match->url_matches) { |
- const size_t term_offset = terms_to_word_starts_offsets[url_match.term_num]; |
- // Advance next_word_starts until it's >= the position of the term we're |
- // considering (adjusted for where the word begins within the term). |
- while ((next_word_starts != end_word_starts) && |
- (*next_word_starts < (url_match.offset + term_offset))) { |
- ++next_word_starts; |
- } |
- const bool at_word_boundary = |
- (next_word_starts != end_word_starts) && |
- (*next_word_starts == url_match.offset + term_offset); |
- if ((question_mark_pos != std::string::npos) && |
- (url_match.offset > question_mark_pos)) { |
- // The match is in a CGI ?... fragment. |
- DCHECK(at_word_boundary); |
- term_scores[url_match.term_num] += 5; |
- } else if ((end_of_hostname_pos != std::string::npos) && |
- (url_match.offset > end_of_hostname_pos)) { |
- // The match is in the path. |
- DCHECK(at_word_boundary); |
- term_scores[url_match.term_num] += 8; |
- } else if ((colon_pos == std::string::npos) || |
- (url_match.offset > colon_pos)) { |
- // The match is in the hostname. |
- if ((last_part_of_hostname_pos == std::string::npos) || |
- (url_match.offset < last_part_of_hostname_pos)) { |
- // Either there are no dots in the hostname or this match isn't |
- // the last dotted component. |
- term_scores[url_match.term_num] += at_word_boundary ? 10 : 2; |
- } else { |
- // The match is in the last part of a dotted hostname (usually this |
- // is the top-level domain .com, .net, etc.). |
- if (allow_tld_matches_) |
- term_scores[url_match.term_num] += at_word_boundary ? 10 : 0; |
- } |
- } else { |
- // The match is in the protocol (a.k.a. scheme). |
- // Matches not at a word boundary should have been filtered already. |
- DCHECK(at_word_boundary); |
- scored_history_match->match_in_scheme = true; |
- if (allow_scheme_matches_) |
- term_scores[url_match.term_num] += 10; |
- } |
- } |
- // Now do the analogous loop over all matches in the title. |
- next_word_starts = word_starts.title_word_starts_.begin(); |
- end_word_starts = word_starts.title_word_starts_.end(); |
- int word_num = 0; |
- scored_history_match->title_matches = FilterTermMatchesByWordStarts( |
- scored_history_match->title_matches, terms_to_word_starts_offsets, |
- word_starts.title_word_starts_, 0, std::string::npos); |
- for (const auto& title_match : scored_history_match->title_matches) { |
- const size_t term_offset = |
- terms_to_word_starts_offsets[title_match.term_num]; |
- // Advance next_word_starts until it's >= the position of the term we're |
- // considering (adjusted for where the word begins within the term). |
- while ((next_word_starts != end_word_starts) && |
- (*next_word_starts < (title_match.offset + term_offset))) { |
- ++next_word_starts; |
- ++word_num; |
- } |
- if (word_num >= 10) |
- break; // only count the first ten words |
- DCHECK(next_word_starts != end_word_starts); |
- DCHECK_EQ(*next_word_starts, title_match.offset + term_offset) |
- << "not at word boundary"; |
- term_scores[title_match.term_num] += 8; |
- } |
- // TODO(mpearson): Restore logic for penalizing out-of-order matches. |
- // (Perhaps discount them by 0.8?) |
- // TODO(mpearson): Consider: if the earliest match occurs late in the string, |
- // should we discount it? |
- // TODO(mpearson): Consider: do we want to score based on how much of the |
- // input string the input covers? (I'm leaning toward no.) |
- |
- // Compute the topicality_score as the sum of transformed term_scores. |
- float topicality_score = 0; |
- for (int term_score : term_scores) { |
- // Drop this URL if it seems like a term didn't appear or, more precisely, |
- // didn't appear in a part of the URL or title that we trust enough |
- // to give it credit for. For instance, terms that appear in the middle |
- // of a CGI parameter get no credit. Almost all the matches dropped |
- // due to this test would look stupid if shown to the user. |
- if (term_score == 0) |
- return 0; |
- topicality_score += raw_term_score_to_topicality_score[std::min( |
- term_score, kMaxRawTermScore - 1)]; |
- } |
- // TODO(mpearson): If there are multiple terms, consider taking the |
- // geometric mean of per-term scores rather than the arithmetic mean. |
- |
- const float final_topicality_score = topicality_score / num_terms; |
- |
- // Demote the URL if the topicality score is less than threshold. |
- if (hqp_experimental_scoring_enabled_ && |
- (final_topicality_score < topicality_threshold_)) { |
- return 0.0; |
- } |
- |
- return final_topicality_score; |
-} |
- |
-// static |
-float ScoredHistoryMatchBuilderImpl::GetRecencyScore(int last_visit_days_ago) { |
- DCHECK(initialized); |
- // Lookup the score in days_ago_to_recency_score, treating |
- // everything older than what we've precomputed as the oldest thing |
- // we've precomputed. The std::max is to protect against corruption |
- // in the database (in case last_visit_days_ago is negative). |
- return days_ago_to_recency_score[std::max( |
- std::min(last_visit_days_ago, kDaysToPrecomputeRecencyScoresFor - 1), 0)]; |
-} |
- |
-// static |
-float ScoredHistoryMatchBuilderImpl::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 |
- // kMaxVisitsToScore as the denominator for the average regardless of |
- // how many visits there were in order to penalize a match that has |
- // fewer visits than kMaxVisitsToScore. |
- float summed_visit_points = 0; |
- const size_t max_visit_to_score = |
- std::min(visits.size(), ScoredHistoryMatch::kMaxVisitsToScore); |
- for (size_t i = 0; i < max_visit_to_score; ++i) { |
- int value_of_transition = |
- (visits[i].second == ui::PAGE_TRANSITION_TYPED) ? 20 : 1; |
- if (bookmarked) |
- value_of_transition = std::max(value_of_transition, bookmark_value_); |
- const float bucket_weight = |
- GetRecencyScore((now - visits[i].first).InDays()); |
- summed_visit_points += (value_of_transition * bucket_weight); |
- } |
- return visits.size() * summed_visit_points / |
- ScoredHistoryMatch::kMaxVisitsToScore; |
-} |
- |
-// static |
-float ScoredHistoryMatchBuilderImpl::GetFinalRelevancyScore( |
- float topicality_score, |
- float frequency_score, |
- const std::vector<ScoreMaxRelevance>& hqp_relevance_buckets) { |
- DCHECK(hqp_relevance_buckets.size() > 0); |
- DCHECK_EQ(hqp_relevance_buckets[0].first, 0.0); |
- |
- 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 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 |
- // - a visit every day, no typed visits -> 0.916 |
- // - a single typed visit yesterday, no other visits -> 2.0 |
- // - 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) |
- // |
- // The below code maps intermediate_score to the range [0, 1399]. |
- // For example: |
- // HQP default scoring buckets: "0.0:400,1.5:600,12.0:1300,20.0:1399" |
- // We will linearly interpolate the scores between: |
- // 0 to 1.5 --> 400 to 600 |
- // 1.5 to 12.0 --> 600 to 1300 |
- // 12.0 to 20.0 --> 1300 to 1399 |
- // >= 20.0 --> 1399 |
- // |
- // The score maxes out at 1399 (i.e., cannot beat a good inlineable result |
- // from HistoryURL provider). |
- const float intermediate_score = topicality_score * frequency_score; |
- |
- // Find the threshold where intermediate score is greater than bucket. |
- size_t i = 1; |
- for (; i < hqp_relevance_buckets.size(); ++i) { |
- const ScoreMaxRelevance& hqp_bucket = hqp_relevance_buckets[i]; |
- if (intermediate_score >= hqp_bucket.first) { |
- continue; |
- } |
- const ScoreMaxRelevance& previous_bucket = hqp_relevance_buckets[i-1]; |
- const float slope = ((hqp_bucket.second - previous_bucket.second) / |
- (hqp_bucket.first - previous_bucket.first)); |
- return (previous_bucket.second + |
- (slope * (intermediate_score - previous_bucket.first))); |
- } |
- // It will reach this stage when the score is > highest bucket score. |
- // Return the highest bucket score. |
- return hqp_relevance_buckets[i-1].second; |
-} |
- |
-// static |
-void ScoredHistoryMatchBuilderImpl::InitHQPExperimentalParams() { |
- // These are default HQP relevance scoring buckets. |
- // See GetFinalRelevancyScore() for details. |
- std::string hqp_relevance_buckets_str = "0.0:400,1.5:600,12.0:1300,20.0:1399"; |
- |
- // Fetch the experiment params if they are any. |
- hqp_experimental_scoring_enabled_ = |
- OmniboxFieldTrial::HQPExperimentalScoringEnabled(); |
- |
- if (hqp_experimental_scoring_enabled_) { |
- // Add the topicality threshold from experiment params. |
- float hqp_experimental_topicality_threhold = |
- OmniboxFieldTrial::HQPExperimentalTopicalityThreshold(); |
- topicality_threshold_ = hqp_experimental_topicality_threhold; |
- |
- // Add the HQP experimental scoring buckets. |
- std::string hqp_experimental_scoring_buckets = |
- OmniboxFieldTrial::HQPExperimentalScoringBuckets(); |
- if (!hqp_experimental_scoring_buckets.empty()) |
- hqp_relevance_buckets_str = hqp_experimental_scoring_buckets; |
- } |
- |
- // Parse the hqp_relevance_buckets_str string once and store them in vector |
- // which is easy to access. |
- hqp_relevance_buckets_ = |
- new std::vector<ScoredHistoryMatchBuilderImpl::ScoreMaxRelevance>(); |
- |
- bool is_valid_bucket_str = GetHQPBucketsFromString(hqp_relevance_buckets_str, |
- hqp_relevance_buckets_); |
- DCHECK(is_valid_bucket_str); |
-} |
- |
-// static |
-bool ScoredHistoryMatchBuilderImpl::GetHQPBucketsFromString( |
- const std::string& buckets_str, |
- std::vector<ScoreMaxRelevance>* hqp_buckets) { |
- DCHECK(hqp_buckets != NULL); |
- DCHECK(!buckets_str.empty()); |
- |
- base::StringPairs kv_pairs; |
- if (base::SplitStringIntoKeyValuePairs(buckets_str, |
- ':', ',', &kv_pairs)) { |
- for (base::StringPairs::const_iterator it = kv_pairs.begin(); |
- it != kv_pairs.end(); ++it) { |
- ScoreMaxRelevance bucket; |
- bool is_valid_intermediate_score = base::StringToDouble(it->first, |
- &bucket.first); |
- DCHECK(is_valid_intermediate_score); |
- bool is_valid_hqp_score = base::StringToInt(it->second, |
- &bucket.second); |
- DCHECK(is_valid_hqp_score); |
- hqp_buckets->push_back(bucket); |
- } |
- return true; |
- } |
- return false; |
-} |