mosesdecoder/moses/src/fuzzy-match/FuzzyMatchWrapper.cpp

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//
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// FuzzyMatchWrapper.cpp
// moses
//
// Created by Hieu Hoang on 26/07/2012.
// Copyright 2012 __MyCompanyName__. All rights reserved.
//
#include <iostream>
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#include "fuzzy-match/FuzzyMatchWrapper.h"
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#include "fuzzy-match/SentenceAlignment.h"
#include "fuzzy-match/Vocabulary.h"
#include "fuzzy-match/Match.h"
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#include "fuzzy-match/create_xml.h"
#include "Util.h"
#include "StaticData.h"
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#include "util/file.hh"
using namespace std;
namespace tmmt
{
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FuzzyMatchWrapper::FuzzyMatchWrapper(const std::string &sourcePath, const std::string &targetPath, const std::string &alignmentPath)
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:basic_flag(false)
,lsed_flag(true)
,refined_flag(true)
,length_filter_flag(true)
,parse_flag(true)
,min_match(70)
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,multiple_flag(true)
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,multiple_slack(0)
,multiple_max(100)
{
// create suffix array
//load_corpus(m_config[0], input);
load_corpus(sourcePath, source);
load_target(targetPath, targetAndAlignment);
load_alignment(alignmentPath, targetAndAlignment);
cerr << "creating suffix array" << endl;
suffixArray = new tmmt::SuffixArray( sourcePath );
cerr << "done creating suffix array" << endl;
}
string FuzzyMatchWrapper::Extract(const string &dirNameStr)
{
const Moses::StaticData &staticData = Moses::StaticData::Instance();
string fuzzyMatchFile = ExtractTM(dirNameStr);
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// create extrac files
create_xml(fuzzyMatchFile);
// create phrase table with usual Moses scoring and consolidate programs
string cmd;
cmd = "LC_ALL=C sort " + fuzzyMatchFile + ".extract | gzip -c > "
+ fuzzyMatchFile + ".extract.sorted.gz";
system(cmd.c_str());
cmd = "LC_ALL=C sort " + fuzzyMatchFile + ".extract.inv | gzip -c > "
+ fuzzyMatchFile + ".extract.inv.sorted.gz";
system(cmd.c_str());
#ifdef IS_XCODE
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cmd = "/Users/hieuhoang/unison/workspace/github/moses-smt/bin";
#elif IS_ECLIPSE
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cmd = "/home/hieu/workspace/github/moses-smt/bin";
#else
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cmd = staticData.GetBinDirectory();
#endif
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cmd += string("/../scripts/training/train-model.perl -dont-zip -first-step 6 -last-step 6 -f en -e fr -hierarchical ")
+ " -extract-file " + fuzzyMatchFile + ".extract -lexical-file - -score-options \"--NoLex\" "
+ " -phrase-translation-table " + fuzzyMatchFile + ".pt";
system(cmd.c_str());
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return fuzzyMatchFile + ".pt.gz";
}
string FuzzyMatchWrapper::ExtractTM(const string &dirNameStr)
{
string inputPath = dirNameStr + "/in";
string fuzzyMatchFile = dirNameStr + "/fuzzyMatchFile";
ofstream fuzzyMatchStream(fuzzyMatchFile.c_str());
vector< vector< WORD_ID > > input;
load_corpus(inputPath, input);
assert(input.size() == 1);
size_t sentenceInd = 0;
clock_t start_clock = clock();
// if (i % 10 == 0) cerr << ".";
// establish some basic statistics
// int input_length = compute_length( input[i] );
int input_length = input[sentenceInd].size();
int best_cost = input_length * (100-min_match) / 100 + 1;
int match_count = 0; // how many substring matches to be considered
//cerr << endl << "sentence " << i << ", length " << input_length << ", best_cost " << best_cost << endl;
// find match ranges in suffix array
vector< vector< pair< SuffixArray::INDEX, SuffixArray::INDEX > > > match_range;
for(size_t start=0;start<input[sentenceInd].size();start++)
{
SuffixArray::INDEX prior_first_match = 0;
SuffixArray::INDEX prior_last_match = suffixArray->GetSize()-1;
vector< string > substring;
bool stillMatched = true;
vector< pair< SuffixArray::INDEX, SuffixArray::INDEX > > matchedAtThisStart;
//cerr << "start: " << start;
for(int word=start; stillMatched && word<input[sentenceInd].size(); word++)
{
substring.push_back( vocabulary.GetWord( input[sentenceInd][word] ) );
// only look up, if needed (i.e. no unnecessary short gram lookups)
// if (! word-start+1 <= short_match_max_length( input_length ) )
// {
SuffixArray::INDEX first_match, last_match;
stillMatched = false;
if (suffixArray->FindMatches( substring, first_match, last_match, prior_first_match, prior_last_match ) )
{
stillMatched = true;
matchedAtThisStart.push_back( make_pair( first_match, last_match ) );
//cerr << " (" << first_match << "," << last_match << ")";
//cerr << " " << ( last_match - first_match + 1 );
prior_first_match = first_match;
prior_last_match = last_match;
}
//}
}
//cerr << endl;
match_range.push_back( matchedAtThisStart );
}
clock_t clock_range = clock();
map< int, vector< Match > > sentence_match;
map< int, int > sentence_match_word_count;
// go through all matches, longest first
for(int length = input[sentenceInd].size(); length >= 1; length--)
{
// do not create matches, if these are handled by the short match function
if (length <= short_match_max_length( input_length ) )
{
continue;
}
unsigned int count = 0;
for(int start = 0; start <= input[sentenceInd].size() - length; start++)
{
if (match_range[start].size() >= length)
{
pair< SuffixArray::INDEX, SuffixArray::INDEX > &range = match_range[start][length-1];
// cerr << " (" << range.first << "," << range.second << ")";
count += range.second - range.first + 1;
for(SuffixArray::INDEX i=range.first; i<=range.second; i++)
{
int position = suffixArray->GetPosition( i );
// sentence length mismatch
size_t sentence_id = suffixArray->GetSentence( position );
int sentence_length = suffixArray->GetSentenceLength( sentence_id );
int diff = abs( (int)sentence_length - (int)input_length );
// cerr << endl << i << "\tsentence " << sentence_id << ", length " << sentence_length;
//if (length <= 2 && input_length>=5 &&
// sentence_match.find( sentence_id ) == sentence_match.end())
// continue;
if (diff > best_cost)
continue;
// compute minimal cost
int start_pos = suffixArray->GetWordInSentence( position );
int end_pos = start_pos + length-1;
// cerr << endl << "\t" << start_pos << "-" << end_pos << " (" << sentence_length << ") vs. "
// << start << "-" << (start+length-1) << " (" << input_length << ")";
// different number of prior words -> cost is at least diff
int min_cost = abs( start - start_pos );
// same number of words, but not sent. start -> cost is at least 1
if (start == start_pos && start>0)
min_cost++;
// different number of remaining words -> cost is at least diff
min_cost += abs( ( sentence_length-1 - end_pos ) -
( input_length-1 - (start+length-1) ) );
// same number of words, but not sent. end -> cost is at least 1
if ( sentence_length-1 - end_pos ==
input_length-1 - (start+length-1)
&& end_pos != sentence_length-1 )
min_cost++;
// cerr << " -> min_cost " << min_cost;
if (min_cost > best_cost)
continue;
// valid match
match_count++;
// compute maximal cost
int max_cost = max( start, start_pos )
+ max( sentence_length-1 - end_pos,
input_length-1 - (start+length-1) );
// cerr << ", max_cost " << max_cost;
Match m = Match( start, start+length-1,
start_pos, start_pos+length-1,
min_cost, max_cost, 0);
sentence_match[ sentence_id ].push_back( m );
sentence_match_word_count[ sentence_id ] += length;
if (max_cost < best_cost)
{
best_cost = max_cost;
if (best_cost == 0) break;
}
//if (match_count >= MAX_MATCH_COUNT) break;
}
}
// cerr << endl;
if (best_cost == 0) break;
//if (match_count >= MAX_MATCH_COUNT) break;
}
// cerr << count << " matches at length " << length << " in " << sentence_match.size() << " tm." << endl;
if (best_cost == 0) break;
//if (match_count >= MAX_MATCH_COUNT) break;
}
cerr << match_count << " matches in " << sentence_match.size() << " sentences." << endl;
clock_t clock_matches = clock();
// consider each sentence for which we have matches
int old_best_cost = best_cost;
int tm_count_word_match = 0;
int tm_count_word_match2 = 0;
int pruned_match_count = 0;
if (short_match_max_length( input_length ))
{
init_short_matches( input[sentenceInd] );
}
vector< int > best_tm;
typedef map< int, vector< Match > >::iterator I;
clock_t clock_validation_sum = 0;
for(I tm=sentence_match.begin(); tm!=sentence_match.end(); tm++)
{
int tmID = tm->first;
int tm_length = suffixArray->GetSentenceLength(tmID);
vector< Match > &match = tm->second;
add_short_matches( match, source[tmID], input_length, best_cost );
//cerr << "match in sentence " << tmID << ": " << match.size() << " [" << tm_length << "]" << endl;
// quick look: how many words are matched
int words_matched = 0;
for(int m=0;m<match.size();m++) {
if (match[m].min_cost <= best_cost) // makes no difference
words_matched += match[m].input_end - match[m].input_start + 1;
}
if (max(input_length,tm_length) - words_matched > best_cost)
{
if (length_filter_flag) continue;
}
tm_count_word_match++;
// prune, check again how many words are matched
vector< Match > pruned = prune_matches( match, best_cost );
words_matched = 0;
for(int p=0;p<pruned.size();p++) {
words_matched += pruned[p].input_end - pruned[p].input_start + 1;
}
if (max(input_length,tm_length) - words_matched > best_cost)
{
if (length_filter_flag) continue;
}
tm_count_word_match2++;
pruned_match_count += pruned.size();
int prior_best_cost = best_cost;
int cost;
clock_t clock_validation_start = clock();
if (! parse_flag ||
pruned.size()>=10) // to prevent worst cases
{
string path;
cost = sed( input[sentenceInd], source[tmID], path, false );
if (cost < best_cost)
{
best_cost = cost;
}
}
else
{
cost = parse_matches( pruned, input_length, tm_length, best_cost );
if (prior_best_cost != best_cost)
{
best_tm.clear();
}
}
clock_validation_sum += clock() - clock_validation_start;
if (cost == best_cost)
{
best_tm.push_back( tmID );
}
}
cerr << "reduced best cost from " << old_best_cost << " to " << best_cost << endl;
cerr << "tm considered: " << sentence_match.size()
<< " word-matched: " << tm_count_word_match
<< " word-matched2: " << tm_count_word_match2
<< " best: " << best_tm.size() << endl;
cerr << "pruned matches: " << ((float)pruned_match_count/(float)tm_count_word_match2) << endl;
// create xml and extract files
string inputStr, sourceStr;
for (size_t pos = 0; pos < input_length; ++pos) {
inputStr += vocabulary.GetWord(input[sentenceInd][pos]) + " ";
}
// do not try to find the best ... report multiple matches
if (multiple_flag) {
int input_letter_length = compute_length( input[sentenceInd] );
for(int si=0; si<best_tm.size(); si++) {
int s = best_tm[si];
string path;
unsigned int letter_cost = sed( input[sentenceInd], source[s], path, true );
// do not report multiple identical sentences, but just their count
//cout << sentenceInd << " "; // sentence number
//cout << letter_cost << "/" << input_letter_length << " ";
//cout << "(" << best_cost <<"/" << input_length <<") ";
//cout << "||| " << s << " ||| " << path << endl;
vector<WORD_ID> &sourceSentence = source[s];
vector<SentenceAlignment> &targets = targetAndAlignment[s];
create_extract(sentenceInd, best_cost, sourceSentence, targets, inputStr, path, fuzzyMatchStream);
}
} // if (multiple_flag)
else {
// find the best matches according to letter sed
string best_path = "";
int best_match = -1;
int best_letter_cost;
if (lsed_flag) {
best_letter_cost = compute_length( input[sentenceInd] ) * min_match / 100 + 1;
for(int si=0; si<best_tm.size(); si++)
{
int s = best_tm[si];
string path;
unsigned int letter_cost = sed( input[sentenceInd], source[s], path, true );
if (letter_cost < best_letter_cost)
{
best_letter_cost = letter_cost;
best_path = path;
best_match = s;
}
}
}
// if letter sed turned off, just compute path for first match
else {
if (best_tm.size() > 0) {
string path;
sed( input[sentenceInd], source[best_tm[0]], path, false );
best_path = path;
best_match = best_tm[0];
}
}
cerr << "elapsed: " << (1000 * (clock()-start_clock) / CLOCKS_PER_SEC)
<< " ( range: " << (1000 * (clock_range-start_clock) / CLOCKS_PER_SEC)
<< " match: " << (1000 * (clock_matches-clock_range) / CLOCKS_PER_SEC)
<< " tm: " << (1000 * (clock()-clock_matches) / CLOCKS_PER_SEC)
<< " (validation: " << (1000 * (clock_validation_sum) / CLOCKS_PER_SEC) << ")"
<< " )" << endl;
if (lsed_flag) {
//cout << best_letter_cost << "/" << compute_length( input[sentenceInd] ) << " (";
}
//cout << best_cost <<"/" << input_length;
if (lsed_flag) {
//cout << ")";
}
//cout << " ||| " << best_match << " ||| " << best_path << endl;
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if (best_match == -1) {
CHECK(source.size());
best_match = 0;
}
// creat xml & extracts
vector<WORD_ID> &sourceSentence = source[best_match];
vector<SentenceAlignment> &targets = targetAndAlignment[best_match];
create_extract(sentenceInd, best_cost, sourceSentence, targets, inputStr, best_path, fuzzyMatchStream);
} // else if (multiple_flag)
fuzzyMatchStream.close();
return fuzzyMatchFile;
}
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void FuzzyMatchWrapper::load_corpus( const std::string &fileName, vector< vector< WORD_ID > > &corpus )
{ // source
ifstream fileStream;
fileStream.open(fileName.c_str());
if (!fileStream) {
cerr << "file not found: " << fileName << endl;
exit(1);
}
cerr << "loading " << fileName << endl;
istream *fileStreamP = &fileStream;
char line[LINE_MAX_LENGTH];
while(true)
{
SAFE_GETLINE((*fileStreamP), line, LINE_MAX_LENGTH, '\n');
if (fileStreamP->eof()) break;
corpus.push_back( vocabulary.Tokenize( line ) );
}
}
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void FuzzyMatchWrapper::load_target(const std::string &fileName, vector< vector< SentenceAlignment > > &corpus)
{
ifstream fileStream;
fileStream.open(fileName.c_str());
if (!fileStream) {
cerr << "file not found: " << fileName << endl;
exit(1);
}
cerr << "loading " << fileName << endl;
istream *fileStreamP = &fileStream;
WORD_ID delimiter = vocabulary.StoreIfNew("|||");
int lineNum = 0;
char line[LINE_MAX_LENGTH];
while(true)
{
SAFE_GETLINE((*fileStreamP), line, LINE_MAX_LENGTH, '\n');
if (fileStreamP->eof()) break;
vector<WORD_ID> toks = vocabulary.Tokenize( line );
corpus.push_back(vector< SentenceAlignment >());
vector< SentenceAlignment > &vec = corpus.back();
vec.push_back(SentenceAlignment());
SentenceAlignment *sentence = &vec.back();
const WORD &countStr = vocabulary.GetWord(toks[0]);
sentence->count = atoi(countStr.c_str());
for (size_t i = 1; i < toks.size(); ++i) {
WORD_ID wordId = toks[i];
if (wordId == delimiter) {
// target and alignments can have multiple sentences.
vec.push_back(SentenceAlignment());
sentence = &vec.back();
// count
++i;
const WORD &countStr = vocabulary.GetWord(toks[i]);
sentence->count = atoi(countStr.c_str());
}
else {
// just a normal word, add
sentence->target.push_back(wordId);
}
}
++lineNum;
}
}
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void FuzzyMatchWrapper::load_alignment(const std::string &fileName, vector< vector< SentenceAlignment > > &corpus )
{
ifstream fileStream;
fileStream.open(fileName.c_str());
if (!fileStream) {
cerr << "file not found: " << fileName << endl;
exit(1);
}
cerr << "loading " << fileName << endl;
istream *fileStreamP = &fileStream;
string delimiter = "|||";
int lineNum = 0;
char line[LINE_MAX_LENGTH];
while(true)
{
SAFE_GETLINE((*fileStreamP), line, LINE_MAX_LENGTH, '\n');
if (fileStreamP->eof()) break;
vector< SentenceAlignment > &vec = corpus[lineNum];
size_t targetInd = 0;
SentenceAlignment *sentence = &vec[targetInd];
vector<string> toks = Moses::Tokenize(line);
for (size_t i = 0; i < toks.size(); ++i) {
string &tok = toks[i];
if (tok == delimiter) {
// target and alignments can have multiple sentences.
++targetInd;
sentence = &vec[targetInd];
++i;
}
else {
// just a normal alignment, add
vector<int> alignPoint = Moses::Tokenize<int>(tok, "-");
assert(alignPoint.size() == 2);
sentence->alignment.push_back(pair<int,int>(alignPoint[0], alignPoint[1]));
}
}
++lineNum;
}
}
/* Letter string edit distance, e.g. sub 'their' to 'there' costs 2 */
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unsigned int FuzzyMatchWrapper::letter_sed( WORD_ID aIdx, WORD_ID bIdx )
{
// check if already computed -> lookup in cache
pair< WORD_ID, WORD_ID > pIdx = make_pair( aIdx, bIdx );
map< pair< WORD_ID, WORD_ID >, unsigned int >::const_iterator lookup = lsed.find( pIdx );
if (lookup != lsed.end())
{
return (lookup->second);
}
// get surface strings for word indices
const string &a = vocabulary.GetWord( aIdx );
const string &b = vocabulary.GetWord( bIdx );
// initialize cost matrix
unsigned int **cost = (unsigned int**) calloc( sizeof( unsigned int* ), a.size()+1 );
for( unsigned int i=0; i<=a.size(); i++ ) {
cost[i] = (unsigned int*) calloc( sizeof(unsigned int), b.size()+1 );
cost[i][0] = i;
}
for( unsigned int j=0; j<=b.size(); j++ ) {
cost[0][j] = j;
}
// core string edit distance loop
for( unsigned int i=1; i<=a.size(); i++ ) {
for( unsigned int j=1; j<=b.size(); j++ ) {
unsigned int ins = cost[i-1][j] + 1;
unsigned int del = cost[i][j-1] + 1;
bool match = (a.substr(i-1,1).compare( b.substr(j-1,1) ) == 0);
unsigned int diag = cost[i-1][j-1] + (match ? 0 : 1);
unsigned int min = (ins < del) ? ins : del;
min = (diag < min) ? diag : min;
cost[i][j] = min;
}
}
// clear out memory
unsigned int final = cost[a.size()][b.size()];
for( unsigned int i=0; i<=a.size(); i++ ) {
free( cost[i] );
}
free( cost );
// cache and return result
lsed[ pIdx ] = final;
return final;
}
/* string edit distance implementation */
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unsigned int FuzzyMatchWrapper::sed( const vector< WORD_ID > &a, const vector< WORD_ID > &b, string &best_path, bool use_letter_sed ) {
// initialize cost and path matrices
unsigned int **cost = (unsigned int**) calloc( sizeof( unsigned int* ), a.size()+1 );
char **path = (char**) calloc( sizeof( char* ), a.size()+1 );
for( unsigned int i=0; i<=a.size(); i++ ) {
cost[i] = (unsigned int*) calloc( sizeof(unsigned int), b.size()+1 );
path[i] = (char*) calloc( sizeof(char), b.size()+1 );
if (i>0)
{
cost[i][0] = cost[i-1][0];
if (use_letter_sed)
{
cost[i][0] += vocabulary.GetWord( a[i-1] ).size();
}
else
{
cost[i][0]++;
}
}
else
{
cost[i][0] = 0;
}
path[i][0] = 'I';
}
for( unsigned int j=0; j<=b.size(); j++ ) {
if (j>0)
{
cost[0][j] = cost[0][j-1];
if (use_letter_sed)
{
cost[0][j] += vocabulary.GetWord( b[j-1] ).size();
}
else
{
cost[0][j]++;
}
}
else
{
cost[0][j] = 0;
}
path[0][j] = 'D';
}
// core string edit distance algorithm
for( unsigned int i=1; i<=a.size(); i++ ) {
for( unsigned int j=1; j<=b.size(); j++ ) {
unsigned int ins = cost[i-1][j];
unsigned int del = cost[i][j-1];
unsigned int match;
if (use_letter_sed)
{
ins += vocabulary.GetWord( a[i-1] ).size();
del += vocabulary.GetWord( b[j-1] ).size();
match = letter_sed( a[i-1], b[j-1] );
}
else
{
ins++;
del++;
match = ( a[i-1] == b[j-1] ) ? 0 : 1;
}
unsigned int diag = cost[i-1][j-1] + match;
char action = (ins < del) ? 'I' : 'D';
unsigned int min = (ins < del) ? ins : del;
if (diag < min)
{
action = (match>0) ? 'S' : 'M';
min = diag;
}
cost[i][j] = min;
path[i][j] = action;
}
}
// construct string for best path
unsigned int i = a.size();
unsigned int j = b.size();
best_path = "";
while( i>0 || j>0 )
{
best_path = path[i][j] + best_path;
if (path[i][j] == 'I')
{
i--;
}
else if (path[i][j] == 'D')
{
j--;
}
else
{
i--;
j--;
}
}
// clear out memory
unsigned int final = cost[a.size()][b.size()];
for( unsigned int i=0; i<=a.size(); i++ ) {
free( cost[i] );
free( path[i] );
}
free( cost );
free( path );
// return result
return final;
}
/* utlility function: compute length of sentence in characters
(spaces do not count) */
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unsigned int FuzzyMatchWrapper::compute_length( const vector< WORD_ID > &sentence )
{
unsigned int length = 0; for( unsigned int i=0; i<sentence.size(); i++ )
{
length += vocabulary.GetWord( sentence[i] ).size();
}
return length;
}
/* brute force method: compare input to all corpus sentences */
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int FuzzyMatchWrapper::basic_fuzzy_match( vector< vector< WORD_ID > > source,
vector< vector< WORD_ID > > input )
{
// go through input set...
for(unsigned int i=0;i<input.size();i++)
{
bool use_letter_sed = false;
// compute sentence length and worst allowed cost
unsigned int input_length;
if (use_letter_sed)
{
input_length = compute_length( input[i] );
}
else
{
input_length = input[i].size();
}
unsigned int best_cost = input_length * (100-min_match) / 100 + 2;
string best_path = "";
int best_match = -1;
// go through all corpus sentences
for(unsigned int s=0;s<source.size();s++)
{
int source_length;
if (use_letter_sed)
{
source_length = compute_length( source[s] );
}
else
{
source_length = source[s].size();
}
int diff = abs((int)source_length - (int)input_length);
if (length_filter_flag && (diff >= best_cost))
{
continue;
}
// compute string edit distance
string path;
unsigned int cost = sed( input[i], source[s], path, use_letter_sed );
// update if new best
if (cost < best_cost)
{
best_cost = cost;
best_path = path;
best_match = s;
}
}
//cout << best_cost << " ||| " << best_match << " ||| " << best_path << endl;
}
}
/* definition of short matches
very short n-gram matches (1-grams) will not be looked up in
the suffix array, since there are too many matches
and for longer sentences, at least one 2-gram match must occur */
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int FuzzyMatchWrapper::short_match_max_length( int input_length )
{
if ( ! refined_flag )
return 0;
if ( input_length >= 5 )
return 1;
return 0;
}
/* if we have non-short matches in a sentence, we need to
take a closer look at it.
this function creates a hash map for all input words and their positions
(to be used by the next function)
(done here, because this has be done only once for an input sentence) */
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void FuzzyMatchWrapper::init_short_matches( const vector< WORD_ID > &input )
{
int max_length = short_match_max_length( input.size() );
if (max_length == 0)
return;
single_word_index.clear();
// store input words and their positions in hash map
for(int i=0; i<input.size(); i++)
{
if (single_word_index.find( input[i] ) == single_word_index.end())
{
vector< int > position_vector;
single_word_index[ input[i] ] = position_vector;
}
single_word_index[ input[i] ].push_back( i );
}
}
/* add all short matches to list of matches for a sentence */
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void FuzzyMatchWrapper::add_short_matches( vector< Match > &match, const vector< WORD_ID > &tm, int input_length, int best_cost )
{
int max_length = short_match_max_length( input_length );
if (max_length == 0)
return;
int tm_length = tm.size();
map< WORD_ID,vector< int > >::iterator input_word_hit;
for(int t_pos=0; t_pos<tm.size(); t_pos++)
{
input_word_hit = single_word_index.find( tm[t_pos] );
if (input_word_hit != single_word_index.end())
{
vector< int > &position_vector = input_word_hit->second;
for(int j=0; j<position_vector.size(); j++)
{
int &i_pos = position_vector[j];
// before match
int max_cost = max( i_pos , t_pos );
int min_cost = abs( i_pos - t_pos );
if ( i_pos>0 && i_pos == t_pos )
min_cost++;
// after match
max_cost += max( (input_length-i_pos) , (tm_length-t_pos));
min_cost += abs( (input_length-i_pos) - (tm_length-t_pos));
if ( i_pos != input_length-1 && (input_length-i_pos) == (tm_length-t_pos))
min_cost++;
if (min_cost <= best_cost)
{
Match new_match( i_pos,i_pos, t_pos,t_pos, min_cost,max_cost,0 );
match.push_back( new_match );
}
}
}
}
}
/* remove matches that are subsumed by a larger match */
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vector< Match > FuzzyMatchWrapper::prune_matches( const vector< Match > &match, int best_cost )
{
//cerr << "\tpruning";
vector< Match > pruned;
for(int i=match.size()-1; i>=0; i--)
{
//cerr << " (" << match[i].input_start << "," << match[i].input_end
// << " ; " << match[i].tm_start << "," << match[i].tm_end
// << " * " << match[i].min_cost << ")";
//if (match[i].min_cost > best_cost)
// continue;
bool subsumed = false;
for(int j=match.size()-1; j>=0; j--)
{
if (i!=j // do not compare match with itself
&& ( match[i].input_end - match[i].input_start <=
match[j].input_end - match[j].input_start ) // i shorter than j
&& ((match[i].input_start == match[j].input_start &&
match[i].tm_start == match[j].tm_start ) ||
(match[i].input_end == match[j].input_end &&
match[i].tm_end == match[j].tm_end) ) )
{
subsumed = true;
}
}
if (! subsumed && match[i].min_cost <= best_cost)
{
//cerr << "*";
pruned.push_back( match[i] );
}
}
//cerr << endl;
return pruned;
}
/* A* parsing method to compute string edit distance */
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int FuzzyMatchWrapper::parse_matches( vector< Match > &match, int input_length, int tm_length, int &best_cost )
{
// cerr << "sentence has " << match.size() << " matches, best cost: " << best_cost << ", lengths input: " << input_length << " tm: " << tm_length << endl;
if (match.size() == 1)
return match[0].max_cost;
if (match.size() == 0)
return input_length+tm_length;
int this_best_cost = input_length + tm_length;
for(int i=0;i<match.size();i++)
{
this_best_cost = min( this_best_cost, match[i].max_cost );
}
// cerr << "\tthis best cost: " << this_best_cost << endl;
// bottom up combination of spans
vector< vector< Match > > multi_match;
multi_match.push_back( match );
int match_level = 1;
while(multi_match[ match_level-1 ].size()>0)
{
// init vector
vector< Match > empty;
multi_match.push_back( empty );
for(int first_level = 0; first_level <= (match_level-1)/2; first_level++)
{
int second_level = match_level - first_level -1;
//cerr << "\tcombining level " << first_level << " and " << second_level << endl;
vector< Match > &first_match = multi_match[ first_level ];
vector< Match > &second_match = multi_match[ second_level ];
for(int i1 = 0; i1 < first_match.size(); i1++) {
for(int i2 = 0; i2 < second_match.size(); i2++) {
// do not combine the same pair twice
if (first_level == second_level && i2 <= i1)
{
continue;
}
// get sorted matches (first is before second)
Match *first, *second;
if (first_match[i1].input_start < second_match[i2].input_start )
{
first = &first_match[i1];
second = &second_match[i2];
}
else
{
second = &first_match[i1];
first = &second_match[i2];
}
//cerr << "\tcombining "
// << "(" << first->input_start << "," << first->input_end << "), "
// << first->tm_start << " [" << first->internal_cost << "]"
// << " with "
// << "(" << second->input_start << "," << second->input_end << "), "
// << second->tm_start<< " [" << second->internal_cost << "]"
// << endl;
// do not process overlapping matches
if (first->input_end >= second->input_start)
{
continue;
}
// no overlap / mismatch in tm
if (first->tm_end >= second->tm_start)
{
continue;
}
// compute cost
int min_cost = 0;
int max_cost = 0;
// initial
min_cost += abs( first->input_start - first->tm_start );
max_cost += max( first->input_start, first->tm_start );
// same number of words, but not sent. start -> cost is at least 1
if (first->input_start == first->tm_start && first->input_start > 0)
{
min_cost++;
}
// in-between
int skipped_words = second->input_start - first->input_end -1;
int skipped_words_tm = second->tm_start - first->tm_end -1;
int internal_cost = max( skipped_words, skipped_words_tm );
internal_cost += first->internal_cost + second->internal_cost;
min_cost += internal_cost;
max_cost += internal_cost;
// final
min_cost += abs( (tm_length-1 - second->tm_end) -
(input_length-1 - second->input_end) );
max_cost += max( (tm_length-1 - second->tm_end),
(input_length-1 - second->input_end) );
// same number of words, but not sent. end -> cost is at least 1
if ( ( input_length-1 - second->input_end
== tm_length-1 - second->tm_end )
&& input_length-1 != second->input_end )
{
min_cost++;
}
// cerr << "\tcost: " << min_cost << "-" << max_cost << endl;
// if worst than best cost, forget it
if (min_cost > best_cost)
{
continue;
}
// add match
Match new_match( first->input_start,
second->input_end,
first->tm_start,
second->tm_end,
min_cost,
max_cost,
internal_cost);
multi_match[ match_level ].push_back( new_match );
// cerr << "\tstored\n";
// possibly updating this_best_cost
if (max_cost < this_best_cost)
{
// cerr << "\tupdating this best cost to " << max_cost << "\n";
this_best_cost = max_cost;
// possibly updating best_cost
if (max_cost < best_cost)
{
// cerr << "\tupdating best cost to " << max_cost << "\n";
best_cost = max_cost;
}
}
}
}
}
match_level++;
}
return this_best_cost;
}
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void FuzzyMatchWrapper::create_extract(int sentenceInd, int cost, const vector< WORD_ID > &sourceSentence, const vector<SentenceAlignment> &targets, const string &inputStr, const string &path, ofstream &outputFile)
{
string sourceStr;
for (size_t pos = 0; pos < sourceSentence.size(); ++pos) {
WORD_ID wordId = sourceSentence[pos];
sourceStr += vocabulary.GetWord(wordId) + " ";
}
for (size_t targetInd = 0; targetInd < targets.size(); ++targetInd) {
const SentenceAlignment &sentenceAlignment = targets[targetInd];
string targetStr = sentenceAlignment.getTargetString(vocabulary);
string alignStr = sentenceAlignment.getAlignmentString();
outputFile
<< sentenceInd << endl
<< cost << endl
<< sourceStr << endl
<< inputStr << endl
<< targetStr << endl
<< alignStr << endl
<< path << endl
<< sentenceAlignment.count << endl;
}
}
} // namespace