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Commit a2c7774d authored by Kang Li's avatar Kang Li
Browse files

Rank apps by Logistic Regression for Smart-Sharing. 

Bug: 30982298
Test: manual - tested by sharing images in Photos and sharing texts in
Chrome.

Change-Id: I9808abdefbc898d3452e684f3462efafdfd53c23
parent 1fd9c8d3

core/java/com/android/internal/app/ChooserActivity.java

+1 −0
Original line number Original line Diff line number Diff line
@@ -563,6 +563,7 @@ public class ChooserActivity extends ResolverActivity { 
            if (ri != null && ri.activityInfo != null) {

            if (ri != null && ri.activityInfo != null) {

                usageStatsManager.reportChooserSelection(ri.activityInfo.packageName, getUserId(),

                usageStatsManager.reportChooserSelection(ri.activityInfo.packageName, getUserId(),

                        annotation, null, info.getResolvedIntent().getAction());

                        annotation, null, info.getResolvedIntent().getAction());

                mResolverComparator.updateModel(info.getResolvedComponentName());

                if (DEBUG) {

                if (DEBUG) {

                    Log.d(TAG, "ResolveInfo Package is" + ri.activityInfo.packageName);

                    Log.d(TAG, "ResolveInfo Package is" + ri.activityInfo.packageName);

                }

                }

core/java/com/android/internal/app/ResolverActivity.java

+1 −1
Original line number Original line Diff line number Diff line
@@ -109,10 +109,10 @@ public class ResolverActivity extends Activity { 
    private boolean mResolvingHome = false;

    private boolean mResolvingHome = false;

    private int mProfileSwitchMessageId = -1;

    private int mProfileSwitchMessageId = -1;

    private final ArrayList<Intent> mIntents = new ArrayList<>();

    private final ArrayList<Intent> mIntents = new ArrayList<>();

    private ResolverComparator mResolverComparator;

    private PickTargetOptionRequest mPickOptionRequest;

    private PickTargetOptionRequest mPickOptionRequest;

    private ComponentName[] mFilteredComponents;

    private ComponentName[] mFilteredComponents;





    protected ResolverComparator mResolverComparator;

    protected ResolverDrawerLayout mResolverDrawerLayout;

    protected ResolverDrawerLayout mResolverDrawerLayout;

    protected String mContentType;

    protected String mContentType;

core/java/com/android/internal/app/ResolverComparator.java

+154 −22
Original line number Original line Diff line number Diff line
@@ -27,11 +27,16 @@ import android.content.pm.ApplicationInfo; 
import android.content.pm.ComponentInfo;

import android.content.pm.ComponentInfo;

import android.content.pm.PackageManager;

import android.content.pm.PackageManager;

import android.content.pm.ResolveInfo;

import android.content.pm.ResolveInfo;

import android.content.SharedPreferences;

import android.os.Environment;

import android.os.storage.StorageManager;

import android.os.UserHandle;

import android.os.UserHandle;

import android.text.TextUtils;

import android.text.TextUtils;

import android.util.ArrayMap;

import android.util.Log;

import android.util.Log;

import com.android.internal.app.ResolverActivity.ResolvedComponentInfo;

import com.android.internal.app.ResolverActivity.ResolvedComponentInfo;





import java.io.File;

import java.text.Collator;

import java.text.Collator;

import java.util.ArrayList;

import java.util.ArrayList;

import java.util.Comparator;

import java.util.Comparator;
@@ -54,6 +59,12 @@ class ResolverComparator implements Comparator<ResolvedComponentInfo> { 




    private static final float RECENCY_MULTIPLIER = 2.f;

    private static final float RECENCY_MULTIPLIER = 2.f;





    // feature names used in ranking.

    private static final String LAUNCH_SCORE = "launch";

    private static final String TIME_SPENT_SCORE = "timeSpent";

    private static final String RECENCY_SCORE = "recency";

    private static final String CHOOSER_SCORE = "chooser";



    private final Collator mCollator;

    private final Collator mCollator;

    private final boolean mHttp;

    private final boolean mHttp;

    private final PackageManager mPm;

    private final PackageManager mPm;
@@ -65,6 +76,7 @@ class ResolverComparator implements Comparator<ResolvedComponentInfo> { 
    private final String mReferrerPackage;

    private final String mReferrerPackage;

    public String mContentType;

    public String mContentType;

    private String mAction;

    private String mAction;

    private LogisticRegressionAppRanker mRanker;





    public ResolverComparator(Context context, Intent intent, String referrerPackage) {

    public ResolverComparator(Context context, Intent intent, String referrerPackage) {

        mCollator = Collator.getInstance(context.getResources().getConfiguration().locale);

        mCollator = Collator.getInstance(context.getResources().getConfiguration().locale);
@@ -80,6 +92,7 @@ class ResolverComparator implements Comparator<ResolvedComponentInfo> { 
        mStats = mUsm.queryAndAggregateUsageStats(mSinceTime, mCurrentTime);

        mStats = mUsm.queryAndAggregateUsageStats(mSinceTime, mCurrentTime);

        mContentType = intent.getType();

        mContentType = intent.getType();

        mAction = intent.getAction();

        mAction = intent.getAction();

        mRanker = new LogisticRegressionAppRanker(context);

    }

    }





    public void compute(List<ResolvedComponentInfo> targets) {

    public void compute(List<ResolvedComponentInfo> targets) {
@@ -152,16 +165,13 @@ class ResolverComparator implements Comparator<ResolvedComponentInfo> { 
        for (ScoredTarget target : mScoredTargets.values()) {

        for (ScoredTarget target : mScoredTargets.values()) {

            final float recency = (float) Math.max(target.lastTimeUsed - recentSinceTime, 0)

            final float recency = (float) Math.max(target.lastTimeUsed - recentSinceTime, 0)

                    / (mostRecentlyUsedTime - recentSinceTime);

                    / (mostRecentlyUsedTime - recentSinceTime);

            final float recencyScore = recency * recency * RECENCY_MULTIPLIER;

            target.setFeatures((float) target.launchCount / mostLaunched,

            final float usageTimeScore = (float) target.timeSpent / mostTimeSpent;

                    (float) target.timeSpent / mostTimeSpent,

            final float launchCountScore = (float) target.launchCount / mostLaunched;

                    recency * recency * RECENCY_MULTIPLIER,



                    (float) target.chooserCount / mostSelected);

            target.score = recencyScore + usageTimeScore + launchCountScore;

            target.selectProb = mRanker.predict(target.getFeatures());

            if (DEBUG) {

            if (DEBUG) {

                Log.d(TAG, "Scores: recencyScore: " + recencyScore

                Log.d(TAG, "Scores: " + target);

                        + " usageTimeScore: " + usageTimeScore

                        + " launchCountScore: " + launchCountScore

                        + " - " + target);

            }

            }

        }

        }

    }

    }
@@ -215,17 +225,11 @@ class ResolverComparator implements Comparator<ResolvedComponentInfo> { 
                final ScoredTarget rhsTarget = mScoredTargets.get(new ComponentName(

                final ScoredTarget rhsTarget = mScoredTargets.get(new ComponentName(

                        rhs.activityInfo.packageName, rhs.activityInfo.name));

                        rhs.activityInfo.packageName, rhs.activityInfo.name));





                final int chooserCountDiff = Long.compare(

                final int selectProbDiff = Float.compare(

                        rhsTarget.chooserCount, lhsTarget.chooserCount);

                        rhsTarget.selectProb, lhsTarget.selectProb);



                if (chooserCountDiff != 0) {

                    return chooserCountDiff > 0 ? 1 : -1;

                }



                final int diff = Float.compare(rhsTarget.score, lhsTarget.score);





                if (diff != 0) {

                if (selectProbDiff != 0) {

                    return diff > 0 ? 1 : -1;

                    return selectProbDiff > 0 ? 1 : -1;

                }

                }

            }

            }

        }

        }
@@ -241,32 +245,160 @@ class ResolverComparator implements Comparator<ResolvedComponentInfo> { 
    public float getScore(ComponentName name) {

    public float getScore(ComponentName name) {

        final ScoredTarget target = mScoredTargets.get(name);

        final ScoredTarget target = mScoredTargets.get(name);

        if (target != null) {

        if (target != null) {

            return target.score;

            return target.selectProb;

        }

        }

        return 0;

        return 0;

    }

    }





    static class ScoredTarget {

    static class ScoredTarget {

        public final ComponentInfo componentInfo;

        public final ComponentInfo componentInfo;

        public float score;

        public long lastTimeUsed;

        public long lastTimeUsed;

        public long timeSpent;

        public long timeSpent;

        public long launchCount;

        public long launchCount;

        public long chooserCount;

        public long chooserCount;

        public ArrayMap<String, Float> features;

        public float selectProb;





        public ScoredTarget(ComponentInfo ci) {

        public ScoredTarget(ComponentInfo ci) {

            componentInfo = ci;

            componentInfo = ci;

            features = new ArrayMap<>(5);

        }

        }





        @Override

        @Override

        public String toString() {

        public String toString() {

            return "ScoredTarget{" + componentInfo

            return "ScoredTarget{" + componentInfo

                    + " score: " + score

                    + " lastTimeUsed: " + lastTimeUsed

                    + " lastTimeUsed: " + lastTimeUsed

                    + " timeSpent: " + timeSpent

                    + " timeSpent: " + timeSpent

                    + " launchCount: " + launchCount

                    + " launchCount: " + launchCount

                    + " chooserCount: " + chooserCount

                    + " chooserCount: " + chooserCount

                    + " selectProb: " + selectProb

                    + "}";

                    + "}";

        }

        }



        public void setFeatures(float launchCountScore, float usageTimeScore, float recencyScore,

                                float chooserCountScore) {

            features.put(LAUNCH_SCORE, launchCountScore);

            features.put(TIME_SPENT_SCORE, usageTimeScore);

            features.put(RECENCY_SCORE, recencyScore);

            features.put(CHOOSER_SCORE, chooserCountScore);

        }



        public ArrayMap<String, Float> getFeatures() {

            return features;

        }

    }



    public void updateModel(ComponentName componentName) {

        if (mScoredTargets == null || componentName == null ||

                !mScoredTargets.containsKey(componentName)) {

            return;

        }

        ScoredTarget selected = mScoredTargets.get(componentName);

        for (ComponentName targetComponent : mScoredTargets.keySet()) {

            if (targetComponent.equals(componentName)) {

                continue;

            }

            ScoredTarget target = mScoredTargets.get(targetComponent);

            // A potential point of optimization. Save updates or derive a closed form for the

            // positive case, to avoid calculating them repeatedly.

            if (target.selectProb >= selected.selectProb) {

                mRanker.update(target.getFeatures(), target.selectProb, false);

                mRanker.update(selected.getFeatures(), selected.selectProb, true);

            }

        }

        mRanker.commitUpdate();

    }



    class LogisticRegressionAppRanker {

        private static final String PARAM_SHARED_PREF_NAME = "resolver_ranker_params";

        private static final String BIAS_PREF_KEY = "bias";

        private static final float LEARNING_RATE = 0.02f;

        private static final float REGULARIZER_PARAM = 0.1f;

        private SharedPreferences mParamSharedPref;

        private ArrayMap<String, Float> mFeatureWeights;

        private float mBias;



        public LogisticRegressionAppRanker(Context context) {

            mParamSharedPref = getParamSharedPref(context);

        }



        public float predict(ArrayMap<String, Float> target) {

            if (target == null || mParamSharedPref == null) {

                return 0.0f;

            }

            final int featureSize = target.size();

            if (featureSize == 0) {

                return 0.0f;

            }

            float sum = 0.0f;

            if (mFeatureWeights == null) {

                mBias = mParamSharedPref.getFloat(BIAS_PREF_KEY, 0.0f);

                mFeatureWeights = new ArrayMap<>(featureSize);

                for (int i = 0; i < featureSize; i++) {

                    String featureName = target.keyAt(i);

                    float weight = mParamSharedPref.getFloat(featureName, 0.0f);

                    sum += weight * target.valueAt(i);

                    mFeatureWeights.put(featureName, weight);

                }

            } else {

                for (int i = 0; i < featureSize; i++) {

                    String featureName = target.keyAt(i);

                    float weight = mFeatureWeights.getOrDefault(featureName, 0.0f);

                    sum += weight * target.valueAt(i);

                }

            }

            return (float) (1.0 / (1.0 + Math.exp(-mBias - sum)));

        }



        public void update(ArrayMap<String, Float> target, float predict, boolean isSelected) {

            if (target == null || target.size() == 0) {

                return;

            }

            final int featureSize = target.size();

            if (mFeatureWeights == null) {

                mBias = 0.0f;

                mFeatureWeights = new ArrayMap<>(featureSize);

            }

            float error = isSelected ? 1.0f - predict : -predict;

            for (int i = 0; i < featureSize; i++) {

                String featureName = target.keyAt(i);

                float currentWeight = mFeatureWeights.getOrDefault(featureName, 0.0f);

                mBias += LEARNING_RATE * error;

                currentWeight = currentWeight - LEARNING_RATE * REGULARIZER_PARAM * currentWeight +

                        LEARNING_RATE * error * target.valueAt(i);

                mFeatureWeights.put(featureName, currentWeight);

            }

            if (DEBUG) {

                Log.d(TAG, "Weights: " + mFeatureWeights + " Bias: " + mBias);

            }

        }



        public void commitUpdate() {

            if (mFeatureWeights == null || mFeatureWeights.size() == 0) {

                return;

            }

            SharedPreferences.Editor editor = mParamSharedPref.edit();

            editor.putFloat(BIAS_PREF_KEY, mBias);

            final int size = mFeatureWeights.size();

            for (int i = 0; i < size; i++) {

                editor.putFloat(mFeatureWeights.keyAt(i), mFeatureWeights.valueAt(i));

            }

            editor.apply();

        }



        private SharedPreferences getParamSharedPref(Context context) {

            // The package info in the context isn't initialized in the way it is for normal apps,

            // so the standard, name-based context.getSharedPreferences doesn't work. Instead, we

            // build the path manually below using the same policy that appears in ContextImpl.

            if (DEBUG) {

                Log.d(TAG, "Context Package Name: " + context.getPackageName());

            }

            final File prefsFile = new File(new File(

                    Environment.getDataUserCePackageDirectory(StorageManager.UUID_PRIVATE_INTERNAL,

                            context.getUserId(), context.getPackageName()),

                    "shared_prefs"),

                    PARAM_SHARED_PREF_NAME + ".xml");

            return context.getSharedPreferences(prefsFile, Context.MODE_PRIVATE);

        }

    }

    }

}
 
}