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LatinIME/native/jni/src/suggest/core/result/suggestions_output_utils.cpp

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/*
* Copyright (C) 2013 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "suggest/core/result/suggestions_output_utils.h"
#include <algorithm>
#include <vector>
#include "suggest/core/dicnode/dic_node.h"
#include "suggest/core/dicnode/dic_node_utils.h"
#include "suggest/core/dictionary/binary_dictionary_shortcut_iterator.h"
#include "suggest/core/dictionary/error_type_utils.h"
#include "suggest/core/policy/scoring.h"
#include "suggest/core/result/suggestion_results.h"
#include "suggest/core/session/dic_traverse_session.h"
#include "suggest/core/suggest_options.h"
namespace latinime {
const int SuggestionsOutputUtils::MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT = 16;
/* static */ void SuggestionsOutputUtils::outputSuggestions(
const Scoring *const scoringPolicy, DicTraverseSession *traverseSession,
const float weightOfLangModelVsSpatialModel,
SuggestionResults *const outSuggestionResults) {
#if DEBUG_EVALUATE_MOST_PROBABLE_STRING
const int terminalSize = 0;
#else
const int terminalSize = traverseSession->getDicTraverseCache()->terminalSize();
#endif
std::vector<DicNode> terminals(terminalSize);
for (int index = terminalSize - 1; index >= 0; --index) {
traverseSession->getDicTraverseCache()->popTerminal(&terminals[index]);
}
// Compute a weight of language model when an invalid weight is passed.
// NOT_A_WEIGHT_OF_LANG_MODEL_VS_SPATIAL_MODEL (-1) is taken as an invalid value.
const float weightOfLangModelVsSpatialModelToOutputSuggestions =
(weightOfLangModelVsSpatialModel < 0.0f)
? scoringPolicy->getAdjustedWeightOfLangModelVsSpatialModel(traverseSession,
terminals.data(), terminalSize)
: weightOfLangModelVsSpatialModel;
outSuggestionResults->setWeightOfLangModelVsSpatialModel(
weightOfLangModelVsSpatialModelToOutputSuggestions);
// Force autocorrection for obvious long multi-word suggestions when the top suggestion is
// a long multiple words suggestion.
// TODO: Implement a smarter auto-commit method for handling multi-word suggestions.
const bool forceCommitMultiWords = scoringPolicy->autoCorrectsToMultiWordSuggestionIfTop()
&& (traverseSession->getInputSize() >= MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT
&& !terminals.empty() && terminals.front().hasMultipleWords());
// TODO: have partial commit work even with multiple pointers.
const bool outputSecondWordFirstLetterInputIndex =
traverseSession->isOnlyOnePointerUsed(0 /* pointerId */);
const bool boostExactMatches = traverseSession->getDictionaryStructurePolicy()->
getHeaderStructurePolicy()->shouldBoostExactMatches();
// Output suggestion results here
for (auto &terminalDicNode : terminals) {
outputSuggestionsOfDicNode(scoringPolicy, traverseSession, &terminalDicNode,
weightOfLangModelVsSpatialModelToOutputSuggestions, boostExactMatches,
forceCommitMultiWords, outputSecondWordFirstLetterInputIndex, outSuggestionResults);
}
scoringPolicy->getMostProbableString(traverseSession,
weightOfLangModelVsSpatialModelToOutputSuggestions, outSuggestionResults);
}
/* static */ bool SuggestionsOutputUtils::shouldBlockWord(
const SuggestOptions *const suggestOptions, const DicNode *const terminalDicNode,
const WordAttributes wordAttributes, const bool isLastWord) {
const bool currentWordExactMatch =
ErrorTypeUtils::isExactMatch(terminalDicNode->getContainedErrorTypes());
// When we have to block offensive words, non-exact matched offensive words should not be
// output.
const bool shouldBlockOffensiveWords = suggestOptions->blockOffensiveWords();
const bool isBlockedOffensiveWord = shouldBlockOffensiveWords &&
wordAttributes.isPossiblyOffensive();
// This function is called in two situations:
//
// 1) At the end of a search, in which case terminalDicNode will point to the last DicNode
// of the search, and isLastWord will be true.
// "fuck"
// |
// \ terminalDicNode (isLastWord=true, currentWordExactMatch=true)
// In this case, if the current word is an exact match, we will always let the word
// through, even if the user is blocking offensive words (it's exactly what they typed!)
//
// 2) In the middle of the search, when we hit a terminal node, to decide whether or not
// to start a new search at root, to try to match the rest of the input. In this case,
// terminalDicNode will point to the terminal node we just hit, and isLastWord will be
// false.
// "fuckvthis"
// |
// \ terminalDicNode (isLastWord=false, currentWordExactMatch=true)
//
// In this case, we should NOT allow the match through (correcting "fuckthis" to "fuck this"
// when offensive words are blocked would be a bad idea).
//
// In the case of a multi-word correction where the offensive word is typed last (eg.
// for the input "allfuck"), this function will be called with isLastWord==true, but
// currentWordExactMatch==false. So we are OK in this case as well.
// "allfuck"
// |
// \ terminalDicNode (isLastWord=true, currentWordExactMatch=false)
if (isLastWord && currentWordExactMatch) {
return false;
} else {
return isBlockedOffensiveWord;
}
}
/* static */ void SuggestionsOutputUtils::outputSuggestionsOfDicNode(
const Scoring *const scoringPolicy, DicTraverseSession *traverseSession,
const DicNode *const terminalDicNode, const float weightOfLangModelVsSpatialModel,
const bool boostExactMatches, const bool forceCommitMultiWords,
const bool outputSecondWordFirstLetterInputIndex,
SuggestionResults *const outSuggestionResults) {
if (DEBUG_GEO_FULL) {
terminalDicNode->dump("OUT:");
}
const float doubleLetterCost =
scoringPolicy->getDoubleLetterDemotionDistanceCost(terminalDicNode);
const float compoundDistance =
terminalDicNode->getCompoundDistance(weightOfLangModelVsSpatialModel)
+ doubleLetterCost;
const WordAttributes wordAttributes = traverseSession->getDictionaryStructurePolicy()
->getWordAttributesInContext(terminalDicNode->getPrevWordIds(),
terminalDicNode->getWordId(), nullptr /* multiBigramMap */);
const bool isExactMatch =
ErrorTypeUtils::isExactMatch(terminalDicNode->getContainedErrorTypes());
const bool isExactMatchWithIntentionalOmission =
ErrorTypeUtils::isExactMatchWithIntentionalOmission(
terminalDicNode->getContainedErrorTypes());
// TODO: Decide whether the word should be auto-corrected or not here.
const bool isAppropriateForAutoCorrection = !ErrorTypeUtils::isMissingExplicitAccent(
terminalDicNode->getContainedErrorTypes());
const int outputTypeFlags =
(wordAttributes.isPossiblyOffensive() ? Dictionary::KIND_FLAG_POSSIBLY_OFFENSIVE : 0)
| ((isExactMatch && boostExactMatches) ? Dictionary::KIND_FLAG_EXACT_MATCH : 0)
| (isExactMatchWithIntentionalOmission ?
Dictionary::KIND_FLAG_EXACT_MATCH_WITH_INTENTIONAL_OMISSION : 0)
| (isAppropriateForAutoCorrection ?
Dictionary::KIND_FLAG_APPROPRIATE_FOR_AUTOCORRECTION : 0);
// Entries that are blacklisted or do not represent a word should not be output.
const bool isValidWord = !(wordAttributes.isBlacklisted() || wordAttributes.isNotAWord());
const bool shouldBlockThisWord = shouldBlockWord(traverseSession->getSuggestOptions(),
terminalDicNode, wordAttributes, true /* isLastWord */);
// Increase output score of top typing suggestion to ensure autocorrection.
// TODO: Better integration with java side autocorrection logic.
const int finalScore = scoringPolicy->calculateFinalScore(
compoundDistance, traverseSession->getInputSize(),
terminalDicNode->getContainedErrorTypes(),
(forceCommitMultiWords && terminalDicNode->hasMultipleWords()),
boostExactMatches, wordAttributes.getProbability() == 0);
// Don't output invalid or blocked offensive words. However, we still need to submit their
// shortcuts if any.
if (isValidWord && !shouldBlockThisWord) {
int codePoints[MAX_WORD_LENGTH];
terminalDicNode->outputResult(codePoints);
const int indexToPartialCommit = outputSecondWordFirstLetterInputIndex ?
terminalDicNode->getSecondWordFirstInputIndex(
traverseSession->getProximityInfoState(0)) :
NOT_AN_INDEX;
outSuggestionResults->addSuggestion(codePoints,
terminalDicNode->getTotalNodeCodePointCount(),
finalScore, Dictionary::KIND_CORRECTION | outputTypeFlags,
indexToPartialCommit, computeFirstWordConfidence(terminalDicNode));
}
// Output shortcuts.
// Shortcut is not supported for multiple words suggestions.
// TODO: Check shortcuts during traversal for multiple words suggestions.
if (!terminalDicNode->hasMultipleWords()) {
BinaryDictionaryShortcutIterator shortcutIt =
traverseSession->getDictionaryStructurePolicy()->getShortcutIterator(
terminalDicNode->getWordId());
const bool sameAsTyped = scoringPolicy->sameAsTyped(traverseSession, terminalDicNode);
outputShortcuts(&shortcutIt, finalScore, sameAsTyped, outSuggestionResults);
}
}
/* static */ int SuggestionsOutputUtils::computeFirstWordConfidence(
const DicNode *const terminalDicNode) {
// Get the number of spaces in the first suggestion
const int spaceCount = terminalDicNode->getTotalNodeSpaceCount();
// Get the number of characters in the first suggestion
const int length = terminalDicNode->getTotalNodeCodePointCount();
// Get the distance for the first word of the suggestion
const float distance = terminalDicNode->getNormalizedCompoundDistanceAfterFirstWord();
// Arbitrarily, we give a score whose useful values range from 0 to 1,000,000.
// 1,000,000 will be the cutoff to auto-commit. It's fine if the number is under 0 or
// above 1,000,000 : under 0 just means it's very bad to commit, and above 1,000,000 means
// we are very confident.
// Expected space count is 1 ~ 5
static const int MIN_EXPECTED_SPACE_COUNT = 1;
static const int MAX_EXPECTED_SPACE_COUNT = 5;
// Expected length is about 4 ~ 30
static const int MIN_EXPECTED_LENGTH = 4;
static const int MAX_EXPECTED_LENGTH = 30;
// Expected distance is about 0.2 ~ 2.0, but consider 0.0 ~ 2.0
static const float MIN_EXPECTED_DISTANCE = 0.0;
static const float MAX_EXPECTED_DISTANCE = 2.0;
// This is not strict: it's where most stuff will be falling, but it's still fine if it's
// outside these values. We want to output a value that reflects all of these. Each factor
// contributes a bit.
// We need at least a space.
if (spaceCount < 1) return NOT_A_FIRST_WORD_CONFIDENCE;
// The smaller the edit distance, the higher the contribution. MIN_EXPECTED_DISTANCE means 0
// contribution, while MAX_EXPECTED_DISTANCE means full contribution according to the
// weight of the distance. Clamp to avoid overflows.
const float clampedDistance = distance < MIN_EXPECTED_DISTANCE ? MIN_EXPECTED_DISTANCE
: distance > MAX_EXPECTED_DISTANCE ? MAX_EXPECTED_DISTANCE : distance;
const int distanceContribution = DISTANCE_WEIGHT_FOR_AUTO_COMMIT
* (MAX_EXPECTED_DISTANCE - clampedDistance)
/ (MAX_EXPECTED_DISTANCE - MIN_EXPECTED_DISTANCE);
// The larger the suggestion length, the larger the contribution. MIN_EXPECTED_LENGTH is no
// contribution, MAX_EXPECTED_LENGTH is full contribution according to the weight of the
// length. Length is guaranteed to be between 1 and 48, so we don't need to clamp.
const int lengthContribution = LENGTH_WEIGHT_FOR_AUTO_COMMIT
* (length - MIN_EXPECTED_LENGTH) / (MAX_EXPECTED_LENGTH - MIN_EXPECTED_LENGTH);
// The more spaces, the larger the contribution. MIN_EXPECTED_SPACE_COUNT space is no
// contribution, MAX_EXPECTED_SPACE_COUNT spaces is full contribution according to the
// weight of the space count.
const int spaceContribution = SPACE_COUNT_WEIGHT_FOR_AUTO_COMMIT
* (spaceCount - MIN_EXPECTED_SPACE_COUNT)
/ (MAX_EXPECTED_SPACE_COUNT - MIN_EXPECTED_SPACE_COUNT);
return distanceContribution + lengthContribution + spaceContribution;
}
/* static */ void SuggestionsOutputUtils::outputShortcuts(
BinaryDictionaryShortcutIterator *const shortcutIt, const int finalScore,
const bool sameAsTyped, SuggestionResults *const outSuggestionResults) {
int shortcutTarget[MAX_WORD_LENGTH];
while (shortcutIt->hasNextShortcutTarget()) {
bool isWhilelist;
int shortcutTargetStringLength;
shortcutIt->nextShortcutTarget(MAX_WORD_LENGTH, shortcutTarget,
&shortcutTargetStringLength, &isWhilelist);
int shortcutScore;
int kind;
if (isWhilelist && sameAsTyped) {
shortcutScore = S_INT_MAX;
kind = Dictionary::KIND_WHITELIST;
} else {
// shortcut entry's score == its base entry's score - 1
shortcutScore = finalScore;
// Protection against int underflow
shortcutScore = std::max(S_INT_MIN + 1, shortcutScore) - 1;
kind = Dictionary::KIND_SHORTCUT;
}
outSuggestionResults->addSuggestion(shortcutTarget, shortcutTargetStringLength,
std::max(S_INT_MIN + 1, shortcutScore) - 1, kind, NOT_AN_INDEX,
NOT_A_FIRST_WORD_CONFIDENCE);
}
}
} // namespace latinime
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