// 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 "chrome/browser/autocomplete/url_prefix.h"
#include "chrome/browser/bookmarks/bookmark_service.h"
#include "chrome/browser/omnibox/omnibox_field_trial.h"
#include "chrome/common/chrome_switches.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::discount_frecency_when_few_visits_ = false;
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,
BookmarkService* bookmark_service)
: 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::string16 url = CleanUpUrlForMatching(gurl, languages);
base::string16 title = 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 frecency_score = GetFrecency(
now, (bookmark_service && bookmark_service->IsBookmarked(gurl)), visits);
raw_score_ = GetFinalRelevancyScore(topicality_score, frecency_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_);
}
}
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::GetFrecency(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.
const int total_sampled_visits = std::min(visits.size(), kMaxVisitsToScore);
if (total_sampled_visits == 0)
return 0.0f;
float summed_visit_points = 0;
for (int i = 0; i < total_sampled_visits; ++i) {
int value_of_transition =
(visits[i].second == content::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 /
(discount_frecency_when_few_visits_ ?
kMaxVisitsToScore : total_sampled_visits);
}
// static
float ScoredHistoryMatch::GetFinalRelevancyScore(float topicality_score,
float frecency_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 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 * frecency_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();
discount_frecency_when_few_visits_ =
OmniboxFieldTrial::HQPDiscountFrecencyWhenFewVisits();
allow_tld_matches_ = OmniboxFieldTrial::HQPAllowMatchInTLDValue();
allow_scheme_matches_ = OmniboxFieldTrial::HQPAllowMatchInSchemeValue();
initialized_ = true;
}
} // namespace history