Chromium Code Reviews| Index: components/ntp_snippets/user_classifier.cc |
| diff --git a/components/ntp_snippets/user_classifier.cc b/components/ntp_snippets/user_classifier.cc |
| index df24ec962f800f5e9c391447525979f662f3c540..60e938c48678c00fe855eb742728746ebef25454 100644 |
| --- a/components/ntp_snippets/user_classifier.cc |
| +++ b/components/ntp_snippets/user_classifier.cc |
| @@ -15,6 +15,8 @@ |
| #include "components/prefs/pref_registry_simple.h" |
| #include "components/prefs/pref_service.h" |
| +namespace ntp_snippets { |
| + |
| namespace { |
| // TODO(jkrcal): Make all of this configurable via variations_service. |
| @@ -33,6 +35,10 @@ const double kMaxHours = 7 * 24; |
| // do not count again). |
| const double kMinHours = 0.5; |
| +// Classification constants. |
| +const double kFrequentUserScrollsAtLeastOncePerHours = 24; |
| +const double kOccasionalUserOpensNTPAtMostOncePerHours = 72; |
| + |
| const char kHistogramAverageHoursToOpenNTP[] = |
| "NewTabPage.UserClassifier.AverageHoursToOpenNTP"; |
| const char kHistogramAverageHoursToShowSuggestions[] = |
| @@ -40,121 +46,257 @@ const char kHistogramAverageHoursToShowSuggestions[] = |
| const char kHistogramAverageHoursToUseSuggestions[] = |
| "NewTabPage.UserClassifier.AverageHoursToUseSuggestions"; |
| -} // namespace |
| +// The enum used for iteration. |
| +const UserClassifier::Metric kMetrics[] = { |
| + UserClassifier::Metric::NTP_OPENED, |
| + UserClassifier::Metric::SUGGESTIONS_SHOWN, |
| + UserClassifier::Metric::SUGGESTIONS_USED}; |
| + |
| +// The summary of the prefs. |
| +const char* kMetricKeys[] = { |
| + prefs::kUserClassifierAverageNTPOpenedPerHour, |
| + prefs::kUserClassifierAverageSuggestionsShownPerHour, |
| + prefs::kUserClassifierAverageSuggestionsUsedPerHour}; |
| +const char* kLastTimeKeys[] = {prefs::kUserClassifierLastTimeToOpenNTP, |
| + prefs::kUserClassifierLastTimeToShowSuggestions, |
| + prefs::kUserClassifierLastTimeToUseSuggestions}; |
| + |
| +// Default lengths of the intervals for new users for the metrics. |
| +const double kDefaults[] = {24, 36, 48}; |
| + |
| +static_assert(arraysize(kMetrics) == |
| + static_cast<int>(UserClassifier::Metric::COUNT) && |
|
Bernhard Bauer
2016/09/20 15:59:54
Maybe split this up into separate asserts?
jkrcal
2016/09/21 08:58:46
I think these checks conceptually belong together,
|
| + arraysize(kMetricKeys) == |
| + static_cast<int>(UserClassifier::Metric::COUNT) && |
| + arraysize(kLastTimeKeys) == |
| + static_cast<int>(UserClassifier::Metric::COUNT) && |
| + arraysize(kDefaults) == |
| + static_cast<int>(UserClassifier::Metric::COUNT), |
| + "Fill in info for all metrics."); |
| + |
| +// Computes the discount rate. |
| +double GetDiscountRatePerHour() { |
| + // Compute discount_rate_per_hour such that |
| + // kDiscountFactorPerDay = 1 - e^{-discount_rate_per_hour * 24}. |
| + return std::log(1.0 / (1.0 - kDiscountFactorPerDay)) / 24.0; |
| +} |
| -namespace ntp_snippets { |
| +// Returns the new value of the metric using its |old_value|, assuming |
| +// |hours_since_last_time| hours have passed since it was last recomputed. |
| +// If |event_now| is true, the event is assumed to have happened right now, |
| +// otherwise no event is assumed to happen within the last |
| +// |hours_since_last_time| hours. |
| +double RecomputeMetric(double old_value, |
| + double hours_since_last_time, |
| + double discount_rate_per_hour, |
| + bool event_now) { |
| + // Compute and store the new discounted average according to the formula |
| + // avg_events := 1 + e^{-discount_rate_per_hour * hours_since} * avg_events. |
| + return (event_now ? 1 : 0) + |
|
Bernhard Bauer
2016/09/20 15:59:54
It might be a bit simpler to have the caller add t
jkrcal
2016/09/21 08:58:46
Done.
|
| + std::exp(-discount_rate_per_hour * hours_since_last_time) * |
| + old_value; |
| +} |
| + |
| +// Compute the number of hours between two events for the given metric value |
| +// assuming the events were equally distributed. |
| +double GetEstimateHoursBetweenEvents(double metric_value, |
| + double discount_rate_per_hour) { |
| + // The computation below is well-defined only for |metric_value| > 1 (log of |
| + // negative value or division by zero). When |metric_value| -> 1, the estimate |
| + // below -> infinity, so kMaxHours is a natural result, here. |
| + if (metric_value <= 1) |
| + return kMaxHours; |
| + |
| + // This is the estimate with the assumption that last event happened right |
| + // now and the system is in the steady-state. Solve estimate_hours in the |
| + // steady-state equation: |
| + // metric_value = 1 + e^{-discount_rate * estimate_hours} * metric_value, |
| + // i.e. |
| + // -discount_rate * estimate_hours = log((metric_value - 1) / metric_value), |
| + // discount_rate * estimate_hours = log(metric_value / (metric_value - 1)), |
| + // estimate_hours = log(metric_value / (metric_value - 1)) / discount_rate. |
| + double estimate_hours = |
| + std::log(metric_value / (metric_value - 1)) / discount_rate_per_hour; |
| + return std::max(kMinHours, std::min(kMaxHours, estimate_hours)); |
| +} |
| + |
| +// The inverse of GetEstimateHoursBetweenEvents(). |
| +double GetMetricValueForEstimateHoursBetweenEvents( |
| + double estimate_hours, |
| + double discount_rate_per_hour) { |
| + // Keep the input value within [kMinHours, kMaxHours]. |
| + estimate_hours = std::max(kMinHours, std::min(kMaxHours, estimate_hours)); |
| + |
| + // Return |metric_value| such that GetEstimateHoursBetweenEvents for |
| + // |metric_value| returns |estimate_hours|. Thus, solve |metric_value| in |
| + // metric_value = 1 + e^{-discount_rate * estimate_hours} * metric_value, |
| + // i.e. |
| + // metric_value * (1 - e^{-discount_rate * estimate_hours}) = 1, |
| + // metric_value = 1 / (1 - e^{-discount_rate * estimate_hours}). |
| + return 1.0 / (1.0 - std::exp(-discount_rate_per_hour * estimate_hours)); |
| +} |
| + |
| +} // namespace |
| UserClassifier::UserClassifier(PrefService* pref_service) |
| : pref_service_(pref_service), |
| - // Compute discount_rate_per_hour such that |
| - // kDiscountFactorPerDay = 1 - e^{-discount_rate_per_hour * 24}. |
| - discount_rate_per_hour_(std::log(1 / (1 - kDiscountFactorPerDay)) / 24) {} |
| + discount_rate_per_hour_(GetDiscountRatePerHour()) { |
| + // The pref_service_ can be null in tests. |
| + if (!pref_service_) |
| + return; |
| + |
| + // Initialize the prefs storing the last time: the counter has just started! |
| + for (const Metric metric : kMetrics) { |
| + if (!HasLastTime(metric)) |
| + SetLastTimeToNow(metric); |
| + } |
| +} |
| UserClassifier::~UserClassifier() {} |
| // static |
| void UserClassifier::RegisterProfilePrefs(PrefRegistrySimple* registry) { |
| - registry->RegisterDoublePref( |
| - prefs::kUserClassifierAverageNTPOpenedPerHour, 1); |
| - registry->RegisterDoublePref( |
| - prefs::kUserClassifierAverageSuggestionsShownPerHour, 1); |
| - registry->RegisterDoublePref( |
| - prefs::kUserClassifierAverageSuggestionsUsedPerHour, 1); |
| - |
| - registry->RegisterInt64Pref(prefs::kUserClassifierLastTimeToOpenNTP, 0); |
| - registry->RegisterInt64Pref(prefs::kUserClassifierLastTimeToShowSuggestions, |
| - 0); |
| - registry->RegisterInt64Pref(prefs::kUserClassifierLastTimeToUseSuggestions, |
| - 0); |
| + for (Metric metric : kMetrics) { |
| + double default_metric_value = GetMetricValueForEstimateHoursBetweenEvents( |
| + kDefaults[static_cast<int>(metric)], GetDiscountRatePerHour()); |
| + registry->RegisterDoublePref(kMetricKeys[static_cast<int>(metric)], |
| + default_metric_value); |
| + registry->RegisterInt64Pref(kLastTimeKeys[static_cast<int>(metric)], 0); |
| + } |
| } |
| -void UserClassifier::OnNTPOpened() { |
| - UpdateMetricOnEvent(prefs::kUserClassifierAverageNTPOpenedPerHour, |
| - prefs::kUserClassifierLastTimeToOpenNTP); |
| +void UserClassifier::OnEvent(Metric metric) { |
| + DCHECK_NE(metric, Metric::COUNT); |
| + double metric_value = UpdateMetricOnEvent(metric); |
| + |
| + double avg = |
| + GetEstimateHoursBetweenEvents(metric_value, discount_rate_per_hour_); |
| + switch (metric) { |
| + case Metric::NTP_OPENED: |
| + UMA_HISTOGRAM_CUSTOM_COUNTS(kHistogramAverageHoursToOpenNTP, avg, 1, |
| + kMaxHours, 50); |
| + break; |
| + case Metric::SUGGESTIONS_SHOWN: |
| + UMA_HISTOGRAM_CUSTOM_COUNTS(kHistogramAverageHoursToShowSuggestions, avg, |
| + 1, kMaxHours, 50); |
| + break; |
| + case Metric::SUGGESTIONS_USED: |
| + UMA_HISTOGRAM_CUSTOM_COUNTS(kHistogramAverageHoursToUseSuggestions, avg, |
| + 1, kMaxHours, 50); |
| + break; |
| + case Metric::COUNT: |
| + NOTREACHED(); |
| + break; |
| + } |
| +} |
| - double avg = GetEstimateHoursBetweenEvents( |
| - prefs::kUserClassifierAverageNTPOpenedPerHour); |
| - UMA_HISTOGRAM_CUSTOM_COUNTS(kHistogramAverageHoursToOpenNTP, avg, 1, |
| - kMaxHours, 50); |
| +double UserClassifier::GetEstimatedAvgTime(Metric metric) const { |
| + DCHECK_NE(metric, Metric::COUNT); |
| + double metric_value = GetUpToDateMetricValue(metric); |
| + return GetEstimateHoursBetweenEvents(metric_value, discount_rate_per_hour_); |
| } |
| -void UserClassifier::OnSuggestionsShown() { |
| - UpdateMetricOnEvent(prefs::kUserClassifierAverageSuggestionsShownPerHour, |
| - prefs::kUserClassifierLastTimeToShowSuggestions); |
| +UserClassifier::UserClass UserClassifier::GetUserClass() const { |
| + if (GetEstimatedAvgTime(Metric::NTP_OPENED) >= |
| + kOccasionalUserOpensNTPAtMostOncePerHours) { |
| + return UserClass::RARE_NTP_USER; |
| + } |
| - double avg = GetEstimateHoursBetweenEvents( |
| - prefs::kUserClassifierAverageSuggestionsShownPerHour); |
| - UMA_HISTOGRAM_CUSTOM_COUNTS(kHistogramAverageHoursToShowSuggestions, avg, 1, |
| - kMaxHours, 50); |
| -} |
| + if (GetEstimatedAvgTime(Metric::SUGGESTIONS_SHOWN) <= |
| + kFrequentUserScrollsAtLeastOncePerHours) { |
| + return UserClass::ACTIVE_SUGGESTIONS_CONSUMER; |
| + } |
| -void UserClassifier::OnSuggestionsUsed() { |
| - UpdateMetricOnEvent(prefs::kUserClassifierAverageSuggestionsUsedPerHour, |
| - prefs::kUserClassifierLastTimeToUseSuggestions); |
| + return UserClass::ACTIVE_NTP_USER; |
| +} |
| - double avg = GetEstimateHoursBetweenEvents( |
| - prefs::kUserClassifierAverageSuggestionsUsedPerHour); |
| - UMA_HISTOGRAM_CUSTOM_COUNTS(kHistogramAverageHoursToUseSuggestions, avg, 1, |
| - kMaxHours, 50); |
| +std::string UserClassifier::GetUserClassDescriptionForDebugging() const { |
| + switch (GetUserClass()) { |
| + case UserClass::RARE_NTP_USER: |
| + return "Rare user of the NTP"; |
| + case UserClass::ACTIVE_NTP_USER: |
| + return "Active user of the NTP"; |
| + case UserClass::ACTIVE_SUGGESTIONS_CONSUMER: |
| + return "Active consumer of NTP suggestions"; |
| + } |
| + NOTREACHED(); |
| + return "Unknown user class"; |
|
Bernhard Bauer
2016/09/20 15:59:54
Just return a std::string, as this is only there t
jkrcal
2016/09/21 08:58:46
Done.
|
| } |
| -void UserClassifier::UpdateMetricOnEvent(const char* metric_pref_name, |
| - const char* last_time_pref_name) { |
| +void UserClassifier::ClearClassificationForDebugging() { |
| + // The pref_service_ can be null in tests. |
| if (!pref_service_) |
| return; |
| + for (const Metric& metric : kMetrics) { |
| + ClearMetricValue(metric); |
| + SetLastTimeToNow(metric); |
| + } |
| +} |
| + |
| +double UserClassifier::UpdateMetricOnEvent(Metric metric) { |
| + // The pref_service_ can be null in tests. |
| + if (!pref_service_) |
| + return 0; |
| + |
| double hours_since_last_time = |
| - std::min(kMaxHours, GetHoursSinceLastTime(last_time_pref_name)); |
| + std::min(kMaxHours, GetHoursSinceLastTime(metric)); |
| // Ignore events within the same "browsing session". |
| if (hours_since_last_time < kMinHours) |
| - return; |
| - SetLastTimeToNow(last_time_pref_name); |
| + return GetUpToDateMetricValue(metric); |
| - double avg_events_per_hour = pref_service_->GetDouble(metric_pref_name); |
| - // Compute and store the new discounted average according to the formula |
| - // avg_events := 1 + e^{-discount_rate_per_hour * hours_since} * avg_events. |
| - double new_avg_events_per_hour = |
| - 1 + |
| - std::exp(-discount_rate_per_hour_ * hours_since_last_time) * |
| - avg_events_per_hour; |
| - pref_service_->SetDouble(metric_pref_name, new_avg_events_per_hour); |
| + SetLastTimeToNow(metric); |
| + |
| + double metric_value = GetMetricValue(metric); |
| + double new_metric_value = |
| + RecomputeMetric(metric_value, hours_since_last_time, |
| + discount_rate_per_hour_, /*event_now=*/true); |
| + SetMetricValue(metric, new_metric_value); |
| + return new_metric_value; |
| } |
| -double UserClassifier::GetEstimateHoursBetweenEvents( |
| - const char* metric_pref_name) { |
| - double avg_events_per_hour = pref_service_->GetDouble(metric_pref_name); |
| +double UserClassifier::GetUpToDateMetricValue(Metric metric) const { |
| + // The pref_service_ can be null in tests. |
| + if (!pref_service_) |
| + return 0; |
| - // Right after the first update, the metric is equal to 1. |
| - if (avg_events_per_hour <= 1) |
| - return kMaxHours; |
| + double hours_since_last_time = |
| + std::min(kMaxHours, GetHoursSinceLastTime(metric)); |
| - // This is the estimate with the assumption that last event happened right |
| - // now and the system is in the steady-state. Solve estimate_hours in the |
| - // steady-state equation: |
| - // avg_events = 1 + e^{-discount_rate * estimate_hours} * avg_events, |
| - // i.e. |
| - // -discount_rate * estimate_hours = log((avg_events - 1) / avg_events), |
| - // discount_rate * estimate_hours = log(avg_events / (avg_events - 1)), |
| - // estimate_hours = log(avg_events / (avg_events - 1)) / discount_rate. |
| - return std::min(kMaxHours, |
| - std::log(avg_events_per_hour / (avg_events_per_hour - 1)) / |
| - discount_rate_per_hour_); |
| + double metric_value = GetMetricValue(metric); |
| + return RecomputeMetric(metric_value, hours_since_last_time, |
| + discount_rate_per_hour_, /*event_now=*/false); |
| } |
| -double UserClassifier::GetHoursSinceLastTime( |
| - const char* last_time_pref_name) { |
| - if (!pref_service_->HasPrefPath(last_time_pref_name)) |
| - return DBL_MAX; |
| +double UserClassifier::GetHoursSinceLastTime(Metric metric) const { |
| + if (!HasLastTime(metric)) |
| + return 0; |
| base::TimeDelta since_last_time = |
| - base::Time::Now() - base::Time::FromInternalValue( |
| - pref_service_->GetInt64(last_time_pref_name)); |
| + base::Time::Now() - base::Time::FromInternalValue(pref_service_->GetInt64( |
| + kLastTimeKeys[static_cast<int>(metric)])); |
| return since_last_time.InSecondsF() / 3600; |
| } |
| -void UserClassifier::SetLastTimeToNow(const char* last_time_pref_name) { |
| - pref_service_->SetInt64(last_time_pref_name, |
| +bool UserClassifier::HasLastTime(Metric metric) const { |
| + return pref_service_->HasPrefPath(kLastTimeKeys[static_cast<int>(metric)]); |
| +} |
| + |
| +void UserClassifier::SetLastTimeToNow(Metric metric) { |
| + pref_service_->SetInt64(kLastTimeKeys[static_cast<int>(metric)], |
| base::Time::Now().ToInternalValue()); |
| } |
| +double UserClassifier::GetMetricValue(Metric metric) const { |
| + return pref_service_->GetDouble(kMetricKeys[static_cast<int>(metric)]); |
| +} |
| + |
| +void UserClassifier::SetMetricValue(Metric metric, double metric_value) { |
| + pref_service_->SetDouble(kMetricKeys[static_cast<int>(metric)], metric_value); |
| +} |
| + |
| +void UserClassifier::ClearMetricValue(Metric metric) { |
| + pref_service_->ClearPref(kMetricKeys[static_cast<int>(metric)]); |
| +} |
| + |
| } // namespace ntp_snippets |