mirror of https://github.com/M66B/FairEmail.git
639 lines
23 KiB
Java
639 lines
23 KiB
Java
package eu.faircode.email;
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/*
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This file is part of FairEmail.
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FairEmail is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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FairEmail is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with FairEmail. If not, see <http://www.gnu.org/licenses/>.
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Copyright 2018-2021 by Marcel Bokhorst (M66B)
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*/
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import android.content.Context;
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import android.content.SharedPreferences;
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import android.os.Build;
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import android.text.TextUtils;
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import androidx.annotation.NonNull;
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import androidx.preference.PreferenceManager;
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import org.jetbrains.annotations.NotNull;
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import org.json.JSONArray;
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import org.json.JSONException;
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import org.json.JSONObject;
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import java.io.File;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.Comparator;
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import java.util.Date;
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import java.util.HashMap;
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import java.util.Iterator;
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import java.util.List;
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import java.util.Map;
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import javax.mail.Address;
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import javax.mail.internet.InternetAddress;
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public class MessageClassifier {
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private static boolean loaded = false;
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private static boolean dirty = false;
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private static final Map<Long, List<String>> accountMsgIds = new HashMap<>();
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private static final Map<Long, Map<String, Integer>> classMessages = new HashMap<>();
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private static final Map<Long, Map<String, Map<String, Frequency>>> wordClassFrequency = new HashMap<>();
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private static final int MAX_WORDS = 1000;
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static void classify(EntityMessage message, EntityFolder folder, EntityFolder target, Context context) {
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try {
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if (!isEnabled(context))
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return;
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if (!folder.auto_classify_source)
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return;
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if (target != null && !target.auto_classify_source)
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return;
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long start = new Date().getTime();
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// Build text to classify
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List<String> texts = getTexts(message, context);
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if (texts.size() == 0)
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return;
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// Load data if needed
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load(context);
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// Initialize account if needed
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if (!accountMsgIds.containsKey(folder.account))
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accountMsgIds.put(folder.account, new ArrayList<>());
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if (!classMessages.containsKey(folder.account))
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classMessages.put(folder.account, new HashMap<>());
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if (!wordClassFrequency.containsKey(folder.account))
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wordClassFrequency.put(folder.account, new HashMap<>());
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// Classify texts
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String classified = classify(folder.account, folder.name, texts, target == null, context);
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long elapsed = new Date().getTime() - start;
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EntityLog.log(context, "Classifier" +
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" folder=" + folder.name +
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" message=" + message.id +
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"@" + new Date(message.received) +
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":" + message.subject +
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" class=" + classified +
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" re=" + message.auto_classified +
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" elapsed=" + elapsed);
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// Auto classify message
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if (classified != null &&
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!classified.equals(folder.name) &&
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!TextUtils.isEmpty(message.msgid) &&
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!accountMsgIds.get(folder.account).contains(message.msgid) &&
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!EntityFolder.JUNK.equals(folder.type)) {
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boolean pro = ActivityBilling.isPro(context);
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DB db = DB.getInstance(context);
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try {
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db.beginTransaction();
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EntityFolder dest = db.folder().getFolderByName(folder.account, classified);
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if (dest != null && dest.auto_classify_target &&
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(pro || EntityFolder.JUNK.equals(dest.type))) {
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EntityOperation.queue(context, message, EntityOperation.MOVE, dest.id, false, true);
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message.ui_hide = true;
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}
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db.setTransactionSuccessful();
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} finally {
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db.endTransaction();
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}
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if (message.ui_hide)
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accountMsgIds.get(folder.account).add(message.msgid);
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}
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dirty = true;
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} catch (Throwable ex) {
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Log.e(ex);
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}
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}
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@NonNull
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private static List<String> getTexts(@NonNull EntityMessage message, @NonNull Context context) throws IOException {
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List<String> texts = new ArrayList<>();
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File file = message.getFile(context);
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if (!file.exists())
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return texts;
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List<Address> addresses = new ArrayList<>();
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if (message.from != null)
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addresses.addAll(Arrays.asList(message.from));
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if (message.to != null)
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addresses.addAll(Arrays.asList(message.to));
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if (message.cc != null)
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addresses.addAll(Arrays.asList(message.cc));
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if (message.bcc != null)
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addresses.addAll(Arrays.asList(message.bcc));
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if (message.reply != null)
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addresses.addAll(Arrays.asList(message.reply));
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for (Address address : addresses) {
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String email = ((InternetAddress) address).getAddress();
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String name = ((InternetAddress) address).getPersonal();
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if (!TextUtils.isEmpty(email))
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texts.add(email);
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if (!TextUtils.isEmpty(name))
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texts.add(name);
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}
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if (message.subject != null)
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texts.add(message.subject);
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String text = HtmlHelper.getFullText(file);
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texts.add(text);
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return texts;
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}
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private static String classify(long account, @NonNull String currentClass, @NonNull List<String> texts, boolean added, @NonNull Context context) {
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State state = new State();
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Log.i("Classifier texts=" + texts.size());
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for (String text : texts) {
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// First word
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processWord(account, added, null, state);
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// Process words
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if (Build.VERSION.SDK_INT < Build.VERSION_CODES.N) {
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java.text.BreakIterator boundary = java.text.BreakIterator.getWordInstance();
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boundary.setText(text);
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int start = boundary.first();
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for (int end = boundary.next(); end != java.text.BreakIterator.DONE; end = boundary.next()) {
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String word = text.substring(start, end);
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processWord(account, added, word, state);
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if (state.words.size() >= MAX_WORDS)
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break;
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start = end;
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}
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} else {
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// The ICU break iterator works better for Chinese texts
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android.icu.text.BreakIterator boundary = android.icu.text.BreakIterator.getWordInstance();
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boundary.setText(text);
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int start = boundary.first();
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for (int end = boundary.next(); end != android.icu.text.BreakIterator.DONE; end = boundary.next()) {
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String word = text.substring(start, end);
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processWord(account, added, word, state);
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if (state.words.size() >= MAX_WORDS)
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break;
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start = end;
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}
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}
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}
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// final word
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processWord(account, added, null, state);
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int maxMessages = 0;
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for (String clazz : classMessages.get(account).keySet()) {
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int count = classMessages.get(account).get(clazz);
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if (count > maxMessages)
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maxMessages = count;
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}
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updateFrequencies(account, currentClass, added, state);
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if (maxMessages == 0) {
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Log.i("Classifier no messages account=" + account);
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return null;
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}
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if (!added)
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return null;
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// Calculate chance per class
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DB db = DB.getInstance(context);
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int words = state.words.size() - texts.size() - 1;
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List<Chance> chances = new ArrayList<>();
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for (String clazz : state.classStats.keySet()) {
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EntityFolder folder = db.folder().getFolderByName(account, clazz);
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if (folder == null) {
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Log.w("Classifier no folder class=" + account + ":" + clazz);
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continue;
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}
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Stat stat = state.classStats.get(clazz);
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double chance = stat.totalFrequency / maxMessages / words;
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Chance c = new Chance(clazz, chance);
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chances.add(c);
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EntityLog.log(context, "Classifier " + c +
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" frequency=" + (Math.round(stat.totalFrequency * 100.0) / 100.0) + "/" + maxMessages + " msgs" +
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" matched=" + stat.matchedWords + "/" + words + " words" +
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" text=" + TextUtils.join(", ", stat.words));
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}
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if (BuildConfig.DEBUG)
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Log.i("Classifier words=" + state.words.size() + " " + TextUtils.join(", ", state.words));
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if (chances.size() <= 1)
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return null;
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// Sort classes by chance
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Collections.sort(chances, new Comparator<Chance>() {
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@Override
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public int compare(Chance c1, Chance c2) {
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return -c1.chance.compareTo(c2.chance);
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}
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});
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SharedPreferences prefs = PreferenceManager.getDefaultSharedPreferences(context);
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double class_min_chance = prefs.getInt("class_min_probability", 15) / 100.0;
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double class_min_difference = prefs.getInt("class_min_difference", 50) / 100.0;
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// Select best class
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String classification = null;
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double c0 = chances.get(0).chance;
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double c1 = chances.get(1).chance;
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double threshold = c0 * (1.0 - class_min_difference);
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if (c0 > class_min_chance && c1 < threshold)
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classification = chances.get(0).clazz;
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Log.i("Classifier current=" + currentClass +
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" c0=" + Math.round(c0 * 100 * 100) / 100.0 + ">" + Math.round(class_min_chance * 100) + "%" +
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" c1=" + Math.round(c1 * 100 * 100) / 100.0 + "<" + Math.round(threshold * 100 * 100) / 100.0 + "%" +
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" (" + Math.round(class_min_difference * 100) + "%)" +
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" classified=" + classification);
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return classification;
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}
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private static void processWord(long account, boolean added, String word, State state) {
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if (word != null) {
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word = word.trim().toLowerCase();
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if (word.length() < 2 || word.matches(".*\\d.*"))
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return;
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}
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if (word != null ||
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state.words.size() == 0 ||
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state.words.get(state.words.size() - 1) != null)
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state.words.add(word);
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if (!added)
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return;
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if (state.words.size() < 3)
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return;
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String before = state.words.get(state.words.size() - 3);
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String current = state.words.get(state.words.size() - 2);
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String after = state.words.get(state.words.size() - 1);
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if (current == null)
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return;
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Map<String, Frequency> classFrequency = wordClassFrequency.get(account).get(current);
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if (classFrequency == null)
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return;
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for (String clazz : classFrequency.keySet()) {
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Frequency frequency = classFrequency.get(clazz);
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if (frequency.count <= 0)
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continue;
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Stat stat = state.classStats.get(clazz);
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if (stat == null) {
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stat = new Stat();
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state.classStats.put(clazz, stat);
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}
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int c = (frequency.count - frequency.duplicates);
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Integer b = (before == null ? null : frequency.before.get(before));
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Integer a = (after == null ? null : frequency.after.get(after));
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double f = (c +
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(b == null ? 2 * c : 2.0 * b / frequency.count * c) +
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(a == null ? 2 * c : 2.0 * a / frequency.count * c)) / 5.0;
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//Log.i("Classifier " +
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// before + "/" + b + "/" + frequency.before.get(before) + " " +
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// after + "/" + a + "/" + frequency.after.get(after) + " " +
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// current + "/" + c + "=" + frequency.count + "-" + frequency.duplicates +
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// " f=" + f);
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stat.totalFrequency += f;
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stat.matchedWords++;
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if (BuildConfig.DEBUG && false)
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stat.words.add(current + "=" + f);
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}
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}
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private static void updateFrequencies(long account, @NonNull String currentClass, boolean added, @NonNull State state) {
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Integer m = classMessages.get(account).get(currentClass);
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m = (m == null ? 0 : m) + (added ? 1 : -1);
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if (m <= 0)
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classMessages.get(account).remove(currentClass);
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else
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classMessages.get(account).put(currentClass, m);
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Log.i("Classifier " + currentClass + "=" + m + " msgs");
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for (int i = 1; i < state.words.size() - 1; i++) {
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String before = state.words.get(i - 1);
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String current = state.words.get(i);
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String after = state.words.get(i + 1);
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if (current == null)
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continue;
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Map<String, Frequency> classFrequency = wordClassFrequency.get(account).get(current);
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if (added) {
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if (classFrequency == null) {
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classFrequency = new HashMap<>();
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wordClassFrequency.get(account).put(current, classFrequency);
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}
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Frequency c = classFrequency.get(currentClass);
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if (c == null) {
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c = new Frequency();
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classFrequency.put(currentClass, c);
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}
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c.add(before, after, 1, state.words.indexOf(current) < i);
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} else {
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Frequency c = (classFrequency == null ? null : classFrequency.get(currentClass));
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if (c != null)
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c.add(before, after, -1, state.words.indexOf(current) < i);
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}
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}
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}
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static synchronized void save(@NonNull Context context) throws JSONException, IOException {
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if (!dirty)
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return;
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File file = getFile(context);
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Helper.writeText(file, toJson().toString(2));
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dirty = false;
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Log.i("Classifier data saved");
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}
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private static synchronized void load(@NonNull Context context) throws IOException, JSONException {
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if (loaded || dirty)
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return;
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wordClassFrequency.clear();
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File file = getFile(context);
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if (file.exists()) {
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String json = Helper.readText(file);
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try {
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fromJson(new JSONObject(json));
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} catch (JSONException ex) {
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Log.e(ex);
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file.delete();
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}
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}
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loaded = true;
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Log.i("Classifier data loaded");
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}
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static synchronized void cleanup(@NonNull Context context) {
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try {
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load(context);
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DB db = DB.getInstance(context);
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for (Long account : accountMsgIds.keySet()) {
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List<String> msgids = accountMsgIds.get(account);
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Log.i("Classifier cleanup account=" + account + " count=" + msgids.size());
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for (String msgid : new ArrayList<>(msgids)) {
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List<EntityMessage> messages = db.message().getMessagesByMsgId(account, msgid);
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if (messages != null && messages.size() == 0) {
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Log.i("Classifier removing msgid=" + msgid);
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msgids.remove(msgid);
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dirty = true;
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}
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}
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}
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if (dirty)
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save(context);
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} catch (Throwable ex) {
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Log.e(ex);
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}
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}
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static synchronized void clear(@NonNull Context context) {
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accountMsgIds.clear();
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wordClassFrequency.clear();
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dirty = true;
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Log.i("Classifier data cleared");
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}
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static boolean isEnabled(@NonNull Context context) {
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SharedPreferences prefs = PreferenceManager.getDefaultSharedPreferences(context);
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return prefs.getBoolean("classification", false);
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}
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static File getFile(@NonNull Context context) {
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return new File(context.getFilesDir(), "classifier.json");
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}
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@NonNull
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static JSONObject toJson() throws JSONException {
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JSONArray jmessages = new JSONArray();
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for (Long account : classMessages.keySet())
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for (String clazz : classMessages.get(account).keySet()) {
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JSONObject jmessage = new JSONObject();
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jmessage.put("account", account);
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jmessage.put("class", clazz);
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jmessage.put("count", classMessages.get(account).get(clazz));
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jmessages.put(jmessage);
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}
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JSONArray jwords = new JSONArray();
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for (Long account : wordClassFrequency.keySet())
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for (String word : wordClassFrequency.get(account).keySet()) {
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Map<String, Frequency> classFrequency = wordClassFrequency.get(account).get(word);
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for (String clazz : classFrequency.keySet()) {
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Frequency f = classFrequency.get(clazz);
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JSONObject jword = new JSONObject();
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jword.put("account", account);
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jword.put("word", word);
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jword.put("class", clazz);
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jword.put("count", f.count);
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jword.put("dup", f.duplicates);
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jword.put("before", from(f.before));
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jword.put("after", from(f.after));
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jwords.put(jword);
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}
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}
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JSONArray jclassified = new JSONArray();
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for (Long account : accountMsgIds.keySet()) {
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JSONObject jaccount = new JSONObject();
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jaccount.put("account", account);
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jaccount.put("messages", from(accountMsgIds.get(account)));
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jclassified.put(jaccount);
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}
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JSONObject jroot = new JSONObject();
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jroot.put("version", 2);
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jroot.put("messages", jmessages);
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jroot.put("words", jwords);
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jroot.put("classified", jclassified);
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return jroot;
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}
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@NonNull
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private static JSONArray from(@NonNull List<String> list) throws JSONException {
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JSONArray jlist = new JSONArray();
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for (String item : list)
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jlist.put(item);
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return jlist;
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}
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@NonNull
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private static JSONObject from(@NonNull Map<String, Integer> map) throws JSONException {
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JSONObject jmap = new JSONObject();
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for (String key : map.keySet())
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jmap.put(key, map.get(key));
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return jmap;
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}
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static void fromJson(@NonNull JSONObject jroot) throws JSONException {
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int version = jroot.optInt("version");
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if (version < 2)
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return;
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JSONArray jmessages = jroot.getJSONArray("messages");
|
|
for (int m = 0; m < jmessages.length(); m++) {
|
|
JSONObject jmessage = (JSONObject) jmessages.get(m);
|
|
long account = jmessage.getLong("account");
|
|
if (!classMessages.containsKey(account))
|
|
classMessages.put(account, new HashMap<>());
|
|
String clazz = jmessage.getString("class");
|
|
int count = jmessage.getInt("count");
|
|
classMessages.get(account).put(clazz, count);
|
|
}
|
|
|
|
JSONArray jwords = jroot.getJSONArray("words");
|
|
for (int w = 0; w < jwords.length(); w++) {
|
|
JSONObject jword = (JSONObject) jwords.get(w);
|
|
long account = jword.getLong("account");
|
|
if (!wordClassFrequency.containsKey(account))
|
|
wordClassFrequency.put(account, new HashMap<>());
|
|
if (jword.has("word")) {
|
|
String word = jword.getString("word");
|
|
Map<String, Frequency> classFrequency = wordClassFrequency.get(account).get(word);
|
|
if (classFrequency == null) {
|
|
classFrequency = new HashMap<>();
|
|
wordClassFrequency.get(account).put(word, classFrequency);
|
|
}
|
|
Frequency f = new Frequency();
|
|
f.count = jword.getInt("count");
|
|
f.duplicates = jword.optInt("dup");
|
|
if (jword.has("before"))
|
|
f.before = from(jword.getJSONObject("before"));
|
|
if (jword.has("after"))
|
|
f.after = from(jword.getJSONObject("after"));
|
|
classFrequency.put(jword.getString("class"), f);
|
|
} else
|
|
Log.w("No words account=" + account);
|
|
}
|
|
|
|
JSONArray jclassified = jroot.getJSONArray("classified");
|
|
for (int a = 0; a < jclassified.length(); a++) {
|
|
JSONObject jaccount = jclassified.getJSONObject(a);
|
|
long account = jaccount.getLong("account");
|
|
List<String> ids = accountMsgIds.get(account);
|
|
if (ids == null) {
|
|
ids = new ArrayList<>();
|
|
accountMsgIds.put(account, ids);
|
|
}
|
|
JSONArray jids = jaccount.getJSONArray("messages");
|
|
for (int h = 0; h < jids.length(); h++)
|
|
ids.add(jids.getString(h));
|
|
}
|
|
}
|
|
|
|
@NonNull
|
|
private static Map<String, Integer> from(@NonNull JSONObject jmap) throws JSONException {
|
|
Map<String, Integer> result = new HashMap<>(jmap.length());
|
|
Iterator<String> iterator = jmap.keys();
|
|
while (iterator.hasNext()) {
|
|
String key = iterator.next();
|
|
result.put(key, jmap.getInt(key));
|
|
}
|
|
return result;
|
|
}
|
|
|
|
private static class State {
|
|
private final List<String> words = new ArrayList<>();
|
|
private final Map<String, Stat> classStats = new HashMap<>();
|
|
}
|
|
|
|
private static class Frequency {
|
|
private int count = 0;
|
|
private int duplicates = 0;
|
|
private Map<String, Integer> before = new HashMap<>();
|
|
private Map<String, Integer> after = new HashMap<>();
|
|
|
|
private void add(String b, String a, int c, boolean duplicate) {
|
|
if (count + c < 0)
|
|
return;
|
|
|
|
count += c;
|
|
|
|
if (duplicate)
|
|
duplicates += c;
|
|
|
|
if (b != null) {
|
|
Integer x = before.get(b);
|
|
before.put(b, (x == null ? 0 : x) + c);
|
|
}
|
|
|
|
if (a != null) {
|
|
Integer x = after.get(a);
|
|
after.put(a, (x == null ? 0 : x) + c);
|
|
}
|
|
}
|
|
}
|
|
|
|
private static class Stat {
|
|
private int matchedWords = 0;
|
|
private double totalFrequency = 0;
|
|
private final List<String> words = new ArrayList<>();
|
|
}
|
|
|
|
private static class Chance {
|
|
private String clazz;
|
|
private Double chance;
|
|
|
|
private Chance(String clazz, Double chance) {
|
|
this.clazz = clazz;
|
|
this.chance = chance;
|
|
}
|
|
|
|
@NotNull
|
|
@Override
|
|
public String toString() {
|
|
return clazz + "=" + Math.round(chance * 100.0 * 100.0) / 100.0 + "%";
|
|
}
|
|
}
|
|
}
|