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** Copyright (C) 2010 Nokia Corporation and/or its subsidiary(-ies).+ −
** All rights reserved.+ −
** Contact: Nokia Corporation (qt-info@nokia.com)+ −
**+ −
** This file is part of the Qt Linguist of the Qt Toolkit.+ −
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** $QT_BEGIN_LICENSE:LGPL$+ −
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** contained in the Technology Preview License Agreement accompanying+ −
** this package.+ −
**+ −
** GNU Lesser General Public License Usage+ −
** Alternatively, this file may be used under the terms of the GNU Lesser+ −
** General Public License version 2.1 as published by the Free Software+ −
** Foundation and appearing in the file LICENSE.LGPL included in the+ −
** packaging of this file. Please review the following information to+ −
** ensure the GNU Lesser General Public License version 2.1 requirements+ −
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** rights. These rights are described in the Nokia Qt LGPL Exception+ −
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** $QT_END_LICENSE$+ −
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****************************************************************************/+ −
+ −
#include "simtexth.h"+ −
#include "translator.h"+ −
+ −
#include <QtCore/QByteArray>+ −
#include <QtCore/QString>+ −
#include <QtCore/QList>+ −
+ −
+ −
QT_BEGIN_NAMESPACE+ −
+ −
typedef QList<TranslatorMessage> TML;+ −
+ −
/*+ −
How similar are two texts? The approach used here relies on co-occurrence+ −
matrices and is very efficient.+ −
+ −
Let's see with an example: how similar are "here" and "hither"? The+ −
co-occurrence matrix M for "here" is M[h,e] = 1, M[e,r] = 1, M[r,e] = 1, and 0+ −
elsewhere; the matrix N for "hither" is N[h,i] = 1, N[i,t] = 1, ...,+ −
N[h,e] = 1, N[e,r] = 1, and 0 elsewhere. The union U of both matrices is the+ −
matrix U[i,j] = max { M[i,j], N[i,j] }, and the intersection V is+ −
V[i,j] = min { M[i,j], N[i,j] }. The score for a pair of texts is+ −
+ −
score = (sum of V[i,j] over all i, j) / (sum of U[i,j] over all i, j),+ −
+ −
a formula suggested by Arnt Gulbrandsen. Here we have+ −
+ −
score = 2 / 6,+ −
+ −
or one third.+ −
+ −
The implementation differs from this in a few details. Most importantly,+ −
repetitions are ignored; for input "xxx", M[x,x] equals 1, not 2.+ −
*/+ −
+ −
/*+ −
Every character is assigned to one of 20 buckets so that the co-occurrence+ −
matrix requires only 20 * 20 = 400 bits, not 256 * 256 = 65536 bits or even+ −
more if we want the whole Unicode. Which character falls in which bucket is+ −
arbitrary.+ −
+ −
The second half of the table is a replica of the first half, because of+ −
laziness.+ −
*/+ −
static const int indexOf[256] = {+ −
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,+ −
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,+ −
// ! " # $ % & ' ( ) * + , - . /+ −
0, 2, 6, 7, 10, 12, 15, 19, 2, 6, 7, 10, 12, 15, 19, 0,+ −
// 0 1 2 3 4 5 6 7 8 9 : ; < = > ?+ −
1, 3, 4, 5, 8, 9, 11, 13, 14, 16, 2, 6, 7, 10, 12, 15,+ −
// @ A B C D E F G H I J K L M N O+ −
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 6, 10, 11, 12, 13, 14,+ −
// P Q R S T U V W X Y Z [ \ ] ^ _+ −
15, 12, 16, 17, 18, 19, 2, 10, 15, 7, 19, 2, 6, 7, 10, 0,+ −
// ` a b c d e f g h i j k l m n o+ −
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 6, 10, 11, 12, 13, 14,+ −
// p q r s t u v w x y z { | } ~+ −
15, 12, 16, 17, 18, 19, 2, 10, 15, 7, 19, 2, 6, 7, 10, 0,+ −
+ −
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,+ −
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,+ −
0, 2, 6, 7, 10, 12, 15, 19, 2, 6, 7, 10, 12, 15, 19, 0,+ −
1, 3, 4, 5, 8, 9, 11, 13, 14, 16, 2, 6, 7, 10, 12, 15,+ −
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 6, 10, 11, 12, 13, 14,+ −
15, 12, 16, 17, 18, 19, 2, 10, 15, 7, 19, 2, 6, 7, 10, 0,+ −
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 6, 10, 11, 12, 13, 14,+ −
15, 12, 16, 17, 18, 19, 2, 10, 15, 7, 19, 2, 6, 7, 10, 0+ −
};+ −
+ −
/*+ −
The entry bitCount[i] (for i between 0 and 255) is the number of bits used to+ −
represent i in binary.+ −
*/+ −
static const int bitCount[256] = {+ −
0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,+ −
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,+ −
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,+ −
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,+ −
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,+ −
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,+ −
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,+ −
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,+ −
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,+ −
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,+ −
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,+ −
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,+ −
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,+ −
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,+ −
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,+ −
4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8+ −
};+ −
+ −
struct CoMatrix+ −
{+ −
/*+ −
The matrix has 20 * 20 = 400 entries. This requires 50 bytes, or 13+ −
words. Some operations are performed on words for more efficiency.+ −
*/+ −
union {+ −
quint8 b[52];+ −
quint32 w[13];+ −
};+ −
+ −
CoMatrix() { memset( b, 0, 52 ); }+ −
+ −
CoMatrix(const QString &str)+ −
{+ −
QByteArray ba = str.toUtf8();+ −
const char *text = ba.constData();+ −
char c = '\0', d;+ −
memset( b, 0, 52 );+ −
/*+ −
The Knuth books are not in the office only for show; they help make+ −
loops 30% faster and 20% as readable.+ −
*/+ −
while ( (d = *text) != '\0' ) {+ −
setCoOccurence( c, d );+ −
if ( (c = *++text) != '\0' ) {+ −
setCoOccurence( d, c );+ −
text++;+ −
}+ −
}+ −
}+ −
+ −
void setCoOccurence( char c, char d ) {+ −
int k = indexOf[(uchar) c] + 20 * indexOf[(uchar) d];+ −
b[k >> 3] |= (1 << (k & 0x7));+ −
}+ −
+ −
int worth() const {+ −
int w = 0;+ −
for ( int i = 0; i < 50; i++ )+ −
w += bitCount[b[i]];+ −
return w;+ −
}+ −
};+ −
+ −
static inline CoMatrix reunion(const CoMatrix &m, const CoMatrix &n)+ −
{+ −
CoMatrix p;+ −
for (int i = 0; i < 13; ++i)+ −
p.w[i] = m.w[i] | n.w[i];+ −
return p;+ −
}+ −
+ −
static inline CoMatrix intersection(const CoMatrix &m, const CoMatrix &n)+ −
{+ −
CoMatrix p;+ −
for (int i = 0; i < 13; ++i)+ −
p.w[i] = m.w[i] & n.w[i];+ −
return p;+ −
}+ −
+ −
StringSimilarityMatcher::StringSimilarityMatcher(const QString &stringToMatch)+ −
{+ −
m_cm = new CoMatrix(stringToMatch);+ −
m_length = stringToMatch.length();+ −
}+ −
+ −
int StringSimilarityMatcher::getSimilarityScore(const QString &strCandidate)+ −
{+ −
CoMatrix cmTarget(strCandidate);+ −
int delta = qAbs(m_length - strCandidate.size());+ −
int score = ( (intersection(*m_cm, cmTarget).worth() + 1) << 10 ) /+ −
( reunion(*m_cm, cmTarget).worth() + (delta << 1) + 1 );+ −
return score;+ −
}+ −
+ −
StringSimilarityMatcher::~StringSimilarityMatcher()+ −
{+ −
delete m_cm;+ −
}+ −
+ −
/**+ −
* Checks how similar two strings are.+ −
* The return value is the score, and a higher score is more similar+ −
* than one with a low score.+ −
* Linguist considers a score over 190 to be a good match.+ −
* \sa StringSimilarityMatcher+ −
*/+ −
int getSimilarityScore(const QString &str1, const QString &str2)+ −
{+ −
CoMatrix cmTarget(str2);+ −
CoMatrix cm(str1);+ −
int delta = qAbs(str1.size() - str2.size());+ −
+ −
int score = ( (intersection(cm, cmTarget).worth() + 1) << 10 )+ −
/ ( reunion(cm, cmTarget).worth() + (delta << 1) + 1 );+ −
+ −
return score;+ −
}+ −
+ −
CandidateList similarTextHeuristicCandidates(const Translator *tor,+ −
const QString &text, int maxCandidates)+ −
{+ −
QList<int> scores;+ −
CandidateList candidates;+ −
+ −
TML all = tor->translatedMessages();+ −
+ −
foreach (const TranslatorMessage &mtm, all) {+ −
if (mtm.type() == TranslatorMessage::Unfinished+ −
|| mtm.translation().isEmpty())+ −
continue;+ −
+ −
QString s = mtm.sourceText();+ −
int score = getSimilarityScore(s, text);+ −
+ −
if (candidates.size() == maxCandidates && score > scores[maxCandidates - 1] )+ −
candidates.removeLast();+ −
+ −
if (candidates.size() < maxCandidates && score >= textSimilarityThreshold) {+ −
Candidate cand( s, mtm.translation() );+ −
+ −
int i;+ −
for (i = 0; i < candidates.size(); i++) {+ −
if (score >= scores.at(i)) {+ −
if (score == scores.at(i)) {+ −
if (candidates.at(i) == cand)+ −
goto continue_outer_loop;+ −
} else {+ −
break;+ −
}+ −
}+ −
}+ −
scores.insert(i, score);+ −
candidates.insert(i, cand);+ −
}+ −
continue_outer_loop:+ −
;+ −
}+ −
return candidates;+ −
}+ −
+ −
QT_END_NAMESPACE+ −