| 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
|
| deleted file mode 100644
|
| index 1f1184c859273b31a94a901238661ce72bd018d8..0000000000000000000000000000000000000000
|
| --- a/chrome/browser/history/scored_history_match.cc
|
| +++ /dev/null
|
| @@ -1,608 +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/history/scored_history_match.h"
|
| -
|
| -#include <algorithm>
|
| -#include <functional>
|
| -#include <iterator>
|
| -#include <numeric>
|
| -#include <set>
|
| -
|
| -#include <math.h>
|
| -
|
| -#include "base/logging.h"
|
| -#include "base/metrics/histogram.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_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 history {
|
| -
|
| -// ScoredHistoryMatch ----------------------------------------------------------
|
| -
|
| -// static
|
| -const size_t ScoredHistoryMatch::kMaxVisitsToScore = 10;
|
| -const int ScoredHistoryMatch::kDaysToPrecomputeRecencyScoresFor = 366;
|
| -const int ScoredHistoryMatch::kMaxRawTermScore = 30;
|
| -float* ScoredHistoryMatch::raw_term_score_to_topicality_score_ = NULL;
|
| -float* ScoredHistoryMatch::days_ago_to_recency_score_ = NULL;
|
| -bool ScoredHistoryMatch::initialized_ = false;
|
| -int ScoredHistoryMatch::bookmark_value_ = 1;
|
| -bool ScoredHistoryMatch::allow_tld_matches_ = false;
|
| -bool ScoredHistoryMatch::allow_scheme_matches_ = false;
|
| -bool ScoredHistoryMatch::also_do_hup_like_scoring_ = false;
|
| -int ScoredHistoryMatch::max_assigned_score_for_non_inlineable_matches_ = -1;
|
| -
|
| -ScoredHistoryMatch::ScoredHistoryMatch()
|
| - : raw_score_(0),
|
| - can_inline_(false) {
|
| - Init();
|
| -}
|
| -
|
| -ScoredHistoryMatch::ScoredHistoryMatch(
|
| - const 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,
|
| - HistoryClient* history_client)
|
| - : HistoryMatch(row, 0, false, false),
|
| - raw_score_(0),
|
| - can_inline_(false) {
|
| - Init();
|
| -
|
| - GURL gurl = row.url();
|
| - if (!gurl.is_valid())
|
| - return;
|
| -
|
| - // 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 (String16Vector::const_iterator iter = terms.begin(); iter != terms.end();
|
| - ++iter, ++term_num) {
|
| - base::string16 term = *iter;
|
| - 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())
|
| - return; // A term was not found in either URL or title - reject.
|
| - url_matches_.insert(url_matches_.end(), url_term_matches.begin(),
|
| - url_term_matches.end());
|
| - title_matches_.insert(title_matches_.end(), title_term_matches.begin(),
|
| - title_term_matches.end());
|
| - }
|
| -
|
| - // 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.)
|
| - url_matches_ = SortAndDeoverlapMatches(url_matches_);
|
| - title_matches_ = SortAndDeoverlapMatches(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...".
|
| - const URLPrefix* best_inlineable_prefix =
|
| - (!url_matches_.empty() && (terms.size() == 1)) ?
|
| - URLPrefix::BestURLPrefix(base::UTF8ToUTF16(gurl.spec()), terms[0]) :
|
| - NULL;
|
| - can_inline_ = (best_inlineable_prefix != NULL) &&
|
| - !IsWhitespace(*(lower_string.rbegin()));
|
| - if (can_inline_) {
|
| - // 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(
|
| - base::UTF8ToUTF16(gurl.spec()), base::string16());
|
| - DCHECK(best_prefix != NULL);
|
| - const int num_components_in_best_prefix = best_prefix->num_components;
|
| - // If the URL is inlineable, we must have a match. Note the prefix that
|
| - // makes it inlineable may be empty.
|
| - DCHECK(best_inlineable_prefix != NULL);
|
| - const int num_components_in_best_inlineable_prefix =
|
| - best_inlineable_prefix->num_components;
|
| - innermost_match = (num_components_in_best_inlineable_prefix ==
|
| - num_components_in_best_prefix);
|
| - }
|
| -
|
| - const float topicality_score = GetTopicalityScore(
|
| - terms.size(), url, terms_to_word_starts_offsets, word_starts);
|
| - const float frequency_score = GetFrequency(
|
| - now, (history_client && history_client->IsBookmarked(gurl)), visits);
|
| - raw_score_ = GetFinalRelevancyScore(topicality_score, frequency_score);
|
| - raw_score_ =
|
| - (raw_score_ <= kint32max) ? static_cast<int>(raw_score_) : kint32max;
|
| -
|
| - if (also_do_hup_like_scoring_ && 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) ||
|
| - (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 && 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.
|
| - raw_score_ = std::max(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 (!can_inline_ && (max_assigned_score_for_non_inlineable_matches_ != -1)) {
|
| - raw_score_ = std::min(max_assigned_score_for_non_inlineable_matches_,
|
| - raw_score_);
|
| - }
|
| -
|
| - // 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(url_matches_);
|
| - base::OffsetAdjuster::UnadjustOffsets(adjustments, &offsets);
|
| - url_matches_ = ReplaceOffsetsInTermMatches(url_matches_, offsets);
|
| -}
|
| -
|
| -ScoredHistoryMatch::~ScoredHistoryMatch() {}
|
| -
|
| -// Comparison function for sorting ScoredMatches by their scores with
|
| -// intelligent tie-breaking.
|
| -bool ScoredHistoryMatch::MatchScoreGreater(const ScoredHistoryMatch& m1,
|
| - const ScoredHistoryMatch& m2) {
|
| - if (m1.raw_score_ != m2.raw_score_)
|
| - return m1.raw_score_ > m2.raw_score_;
|
| -
|
| - // This tie-breaking logic is inspired by / largely copied from the
|
| - // ordering logic in history_url_provider.cc CompareHistoryMatch().
|
| -
|
| - // A URL that has been typed at all is better than one that has never been
|
| - // typed. (Note "!"s on each side.)
|
| - if (!m1.url_info.typed_count() != !m2.url_info.typed_count())
|
| - return m1.url_info.typed_count() > m2.url_info.typed_count();
|
| -
|
| - // Innermost matches (matches after any scheme or "www.") are better than
|
| - // non-innermost matches.
|
| - if (m1.innermost_match != m2.innermost_match)
|
| - return m1.innermost_match;
|
| -
|
| - // URLs that have been typed more often are better.
|
| - if (m1.url_info.typed_count() != m2.url_info.typed_count())
|
| - return m1.url_info.typed_count() > m2.url_info.typed_count();
|
| -
|
| - // For URLs that have each been typed once, a host (alone) is better
|
| - // than a page inside.
|
| - if (m1.url_info.typed_count() == 1) {
|
| - if (m1.IsHostOnly() != m2.IsHostOnly())
|
| - return m1.IsHostOnly();
|
| - }
|
| -
|
| - // URLs that have been visited more often are better.
|
| - if (m1.url_info.visit_count() != m2.url_info.visit_count())
|
| - return m1.url_info.visit_count() > m2.url_info.visit_count();
|
| -
|
| - // URLs that have been visited more recently are better.
|
| - return m1.url_info.last_visit() > m2.url_info.last_visit();
|
| -}
|
| -
|
| -// static
|
| -TermMatches ScoredHistoryMatch::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 (TermMatches::const_iterator iter = term_matches.begin();
|
| - iter != term_matches.end(); ++iter) {
|
| - const size_t term_offset = terms_to_word_starts_offsets[iter->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 < (iter->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 ((iter->offset < start_pos) ||
|
| - ((end_pos != std::string::npos) && (iter->offset >= end_pos)) ||
|
| - ((next_word_starts != end_word_starts) &&
|
| - (*next_word_starts == iter->offset + term_offset)))
|
| - filtered_matches.push_back(*iter);
|
| - }
|
| - return filtered_matches;
|
| -}
|
| -
|
| -float ScoredHistoryMatch::GetTopicalityScore(
|
| - const int num_terms,
|
| - const base::string16& url,
|
| - const WordStarts& terms_to_word_starts_offsets,
|
| - const RowWordStarts& word_starts) {
|
| - // Because the below thread 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.)
|
| - DCHECK(!content::BrowserThread::IsThreadInitialized(
|
| - content::BrowserThread::UI) ||
|
| - content::BrowserThread::CurrentlyOn(content::BrowserThread::UI));
|
| - if (raw_term_score_to_topicality_score_ == NULL) {
|
| - raw_term_score_to_topicality_score_ = new float[kMaxRawTermScore];
|
| - FillInTermScoreToTopicalityScoreArray();
|
| - }
|
| - // 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).
|
| - url_matches_ = FilterTermMatchesByWordStarts(
|
| - 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.
|
| - url_matches_ = FilterTermMatchesByWordStarts(
|
| - url_matches_, terms_to_word_starts_offsets,
|
| - word_starts.url_word_starts_, 0, colon_pos);
|
| - }
|
| - for (TermMatches::const_iterator iter = url_matches_.begin();
|
| - iter != url_matches_.end(); ++iter) {
|
| - const size_t term_offset = terms_to_word_starts_offsets[iter->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 < (iter->offset + term_offset))) {
|
| - ++next_word_starts;
|
| - }
|
| - const bool at_word_boundary = (next_word_starts != end_word_starts) &&
|
| - (*next_word_starts == iter->offset + term_offset);
|
| - if ((question_mark_pos != std::string::npos) &&
|
| - (iter->offset > question_mark_pos)) {
|
| - // The match is in a CGI ?... fragment.
|
| - DCHECK(at_word_boundary);
|
| - term_scores[iter->term_num] += 5;
|
| - } else if ((end_of_hostname_pos != std::string::npos) &&
|
| - (iter->offset > end_of_hostname_pos)) {
|
| - // The match is in the path.
|
| - DCHECK(at_word_boundary);
|
| - term_scores[iter->term_num] += 8;
|
| - } else if ((colon_pos == std::string::npos) ||
|
| - (iter->offset > colon_pos)) {
|
| - // The match is in the hostname.
|
| - if ((last_part_of_hostname_pos == std::string::npos) ||
|
| - (iter->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[iter->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[iter->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);
|
| - match_in_scheme = true;
|
| - if (allow_scheme_matches_)
|
| - term_scores[iter->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;
|
| - title_matches_ = FilterTermMatchesByWordStarts(
|
| - title_matches_, terms_to_word_starts_offsets,
|
| - word_starts.title_word_starts_, 0, std::string::npos);
|
| - for (TermMatches::const_iterator iter = title_matches_.begin();
|
| - iter != title_matches_.end(); ++iter) {
|
| - const size_t term_offset = terms_to_word_starts_offsets[iter->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 < (iter->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, iter->offset + term_offset)
|
| - << "not at word boundary";
|
| - term_scores[iter->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 (size_t i = 0; i < term_scores.size(); ++i) {
|
| - // 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_scores[i] == 0)
|
| - return 0;
|
| - topicality_score += raw_term_score_to_topicality_score_[
|
| - (term_scores[i] >= kMaxRawTermScore) ? (kMaxRawTermScore - 1) :
|
| - term_scores[i]];
|
| - }
|
| - // TODO(mpearson): If there are multiple terms, consider taking the
|
| - // geometric mean of per-term scores rather than the arithmetic mean.
|
| -
|
| - return topicality_score / num_terms;
|
| -}
|
| -
|
| -// static
|
| -void ScoredHistoryMatch::FillInTermScoreToTopicalityScoreArray() {
|
| - 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;
|
| - }
|
| -}
|
| -
|
| -// static
|
| -float ScoredHistoryMatch::GetRecencyScore(int last_visit_days_ago) {
|
| - // Because the below thread 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.)
|
| - DCHECK(!content::BrowserThread::IsThreadInitialized(
|
| - content::BrowserThread::UI) ||
|
| - content::BrowserThread::CurrentlyOn(content::BrowserThread::UI));
|
| - if (days_ago_to_recency_score_ == NULL) {
|
| - days_ago_to_recency_score_ = new float[kDaysToPrecomputeRecencyScoresFor];
|
| - FillInDaysAgoToRecencyScoreArray();
|
| - }
|
| - // 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)];
|
| -}
|
| -
|
| -void ScoredHistoryMatch::FillInDaysAgoToRecencyScoreArray() {
|
| - 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]);
|
| - }
|
| - }
|
| -}
|
| -
|
| -// static
|
| -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
|
| - // 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;
|
| - for (size_t i = 0; i < std::min(visits.size(), kMaxVisitsToScore); ++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 / kMaxVisitsToScore;
|
| -}
|
| -
|
| -// static
|
| -float ScoredHistoryMatch::GetFinalRelevancyScore(float topicality_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 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)
|
| - 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) {
|
| - // Linearly extrapolate between 0 and 1.5 so 0 has a score of 400
|
| - // and 1.5 has a score of 600.
|
| - const float slope = (600 - 400) / (1.5f - 0.0f);
|
| - return 400 + slope * intermediate_score;
|
| - }
|
| - if (intermediate_score <= 12.0) {
|
| - // Linearly extrapolate up to 12 so 12 has a score of 1300.
|
| - const float slope = (1300 - 600) / (12.0f - 1.5f);
|
| - return 600 + slope * (intermediate_score - 1.5);
|
| - }
|
| - // Linearly extrapolate so a score of 20 (or more) has a score of 1399.
|
| - // (Scores above 20 are possible for URLs that have multiple term hits
|
| - // in the URL and/or title and that are visited practically all
|
| - // the time using typed visits. We don't attempt to distinguish
|
| - // between these very good results.)
|
| - const float slope = (1399 - 1300) / (20.0f - 12.0f);
|
| - return std::min(1399.0, 1300 + slope * (intermediate_score - 12.0));
|
| -}
|
| -
|
| -void ScoredHistoryMatch::Init() {
|
| - if (initialized_)
|
| - return;
|
| - also_do_hup_like_scoring_ = false;
|
| - // 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 (also_do_hup_like_scoring_) {
|
| - max_assigned_score_for_non_inlineable_matches_ =
|
| - HistoryURLProvider::kScoreForBestInlineableResult - 1;
|
| - }
|
| - bookmark_value_ = OmniboxFieldTrial::HQPBookmarkValue();
|
| - allow_tld_matches_ = OmniboxFieldTrial::HQPAllowMatchInTLDValue();
|
| - allow_scheme_matches_ = OmniboxFieldTrial::HQPAllowMatchInSchemeValue();
|
| - initialized_ = true;
|
| -}
|
| -
|
| -} // namespace history
|
|
|