void CTime::serialize(CDictionary& toDictionary) const
{
toDictionary.setValueForKey(cMillisecondsKey, milliseconds());
toDictionary.setValueForKey(cSecondsKey, seconds());
toDictionary.setValueForKey(cMinutesKey, minutes());
toDictionary.setValueForKey(cHoursKey, hours());
}
//对字符串用最大匹配法（正向或逆向）处理
string SegmentSentence(string s1)
{
string s2 = ""; //用s2存放分词结果
while (!s1.empty())
{
int len = (int)s1.length(); // 取输入串长度
if (len > MaxWordLength) // 如果输入串长度大于最大词长
{
len = MaxWordLength; // 只在最大词长范围内进行处理
}
//string w = s1.substr(0, len); // （正向用）将输入串左边等于最大词长长度串取出作为候选词
string w = s1.substr(s1.length() - len, len); //逆向用
int n = WordDic.FindWord(w); // 在词典中查找相应的词
while (len > 2 && n == 0) // 如果不是词
{
len -= 2; // 从候选词右边减掉一个汉字，将剩下的部分作为候选词
//w = w.substr(0, len); //正向用
w = s1.substr(s1.length() - len, len); //逆向用
n = WordDic.FindWord(w);
}
//s2 += w + Separator; // (正向用）将匹配得到的词连同词界标记加到输出串末尾
w = w + Separator; // (逆向用)
s2 = w + s2; // (逆向用)
//s1 = s1.substr(w.length(), s1.length()); //(正向用)从s1-w处开始
s1 = s1.substr(0, s1.length() - len); // (逆向用)
}
return s2;
}
/*
* логика внутри цикла метода может показаться запутанной и тяжеловатой
* для сопровождения. Собственно, это было сделано в пользу малого размера словаря
* при желании его можно сделать более пригодным для сопровождения
*/
string Translate(int num,int power)
{
string result;
int temp;
vector<int> digits;
char buff[100];
digits=Num2Digits(num,power);
vector<int>::iterator it=digits.begin();
vector<int>::iterator end=digits.end();
int dig=digits.size()-1;
while(it!=end)
{
switch(dig%3)
{
case 0: {
sprintf(buff,"d%d%d", dig ,*it );
result+=D.GetTranslate(buff) + " ";
break;
}
case 1: {
if(*it)
{
if(*it==1)
{
temp=10*(*it);
++it;
--dig;
temp+=(*it);
sprintf(buff,"%d", temp );
result+=D.GetTranslate(buff) + " ";
sprintf(buff,"d%d0", dig );
result+=D.GetTranslate(buff) + " ";
}
else
{
sprintf(buff,"%d", *it*10 );
result+=D.GetTranslate(buff) + " ";
}
}
break;
}
case 2: {
if(*it)
{
sprintf(buff,"%d", *it*100 );
result+=D.GetTranslate(buff) + " ";
}
break;
}
}
--dig;
++it;
}
return result;
}
//CDynamicArray &aWord: the words array
//CDynamicArray &aWordBinaryNet:the net between words
//double dSmoothingPara: the parameter of data smoothing
//CDictionary &DictBinary: the binary dictionary
//CDictionary &DictCore: the Core dictionary
bool CSegment::BiGraphGenerate(CDynamicArray &aWord, CDynamicArray &aBinaryWordNet,double dSmoothingPara,CDictionary &DictBinary,CDictionary &DictCore)
{
PARRAY_CHAIN pTail,pCur,pNextWords;//Temp buffer
unsigned int nWordIndex=0,nTwoWordsFreq=0,nCurWordIndex,nNextWordIndex;
//nWordIndex: the index number of current word
double dCurFreqency,dValue,dTemp;
char sTwoWords[WORD_MAXLENGTH];
m_nWordCount=aWord.GetTail(&pTail);//Get tail element and return the words count
if(m_npWordPosMapTable)
{//free buffer
delete [] m_npWordPosMapTable;
m_npWordPosMapTable=0;
}
if(m_nWordCount>0)//Word count is greater than 0
{
m_npWordPosMapTable=new int[m_nWordCount];//Record the position of possible words
memset(m_npWordPosMapTable,0,m_nWordCount*sizeof(int));
}
pCur=aWord.GetHead();
while(pCur!=NULL)//Set the position map of words
{
m_npWordPosMapTable[nWordIndex++]=pCur->row*MAX_SENTENCE_LEN+pCur->col;
pCur=pCur->next;
}
pCur=aWord.GetHead();
while(pCur!=NULL)//
{
if(pCur->nPOS>=0)//It's not an unknown words
dCurFreqency=pCur->value;
else//Unknown words
dCurFreqency=DictCore.GetFrequency(pCur->sWord,2);
aWord.GetElement(pCur->col,-1,pCur,&pNextWords);//Get next words which begin with pCur->col
while(pNextWords&&pNextWords->row==pCur->col)//Next words
{
//Current words frequency
strcpy(sTwoWords,pCur->sWord);
strcat(sTwoWords,WORD_SEGMENTER);
strcat(sTwoWords,pNextWords->sWord);
nTwoWordsFreq=DictBinary.GetFrequency(sTwoWords,3);
//Two linked Words frequency
dTemp=(double)1/MAX_FREQUENCE;
//Smoothing
dValue=-log(dSmoothingPara*(1+dCurFreqency)/(MAX_FREQUENCE+80000)+(1-dSmoothingPara)*((1-dTemp)*nTwoWordsFreq/(1+dCurFreqency)+dTemp));
//-log{a*P(Ci-1)+(1-a)P(Ci|Ci-1)} Note 0<a<1
if(pCur->nPOS<0)//Unknown words: P(Wi|Ci);while known words:1
dValue+=pCur->value;
//Get the position index of current word in the position map table
nCurWordIndex=BinarySearch(pCur->row*MAX_SENTENCE_LEN+pCur->col,m_npWordPosMapTable,m_nWordCount);
nNextWordIndex=BinarySearch(pNextWords->row*MAX_SENTENCE_LEN+pNextWords->col,m_npWordPosMapTable,m_nWordCount);
aBinaryWordNet.SetElement(nCurWordIndex,nNextWordIndex,dValue,pCur->nPOS);
pNextWords=pNextWords->next;//Get next word
}
pCur=pCur->next;
}
return true;
}
void CTime::deserialize(const CDictionary& fromDictionary)
{
UInt32 ms = fromDictionary.valueAsUInt32ForKey(cMillisecondsKey);
UInt32 s = fromDictionary.valueAsUInt32ForKey(cSecondsKey);
UInt32 m = fromDictionary.valueAsUInt32ForKey(cMinutesKey);
UInt32 h = fromDictionary.valueAsUInt32ForKey(cHoursKey);
mData = h * MILLISECONDS_IN_HOUR +
m * MILLISECONDS_IN_MINUTE +
s * MILLISECONDS_IN_SECOND +
ms;
}
//POS tagging with Hidden Markov Model
bool CSpan::POSTagging(PWORD_RESULT pWordItems,CDictionary &dictCore,CDictionary &dictUnknown)
{
//pWordItems: Items; nItemCount: the count of items;core dictionary and unknown recognition dictionary
int i=0,j,nStartPos;
Reset(false);
while(i>-1&&pWordItems[i].sWord[0]!=0)
{
nStartPos=i;//Start Position
i=GetFrom(pWordItems,nStartPos,dictCore,dictUnknown);
GetBestPOS();
switch(m_tagType)
{
case TT_NORMAL://normal POS tagging
j=1;
while(m_nBestTag[j]!=-1&&j<m_nCurLength)
{//Store the best POS tagging
pWordItems[j+nStartPos-1].nHandle=m_nBestTag[j];
//Let 。be 0
if(pWordItems[j+nStartPos-1].dValue>0&&dictCore.IsExist(pWordItems[j+nStartPos-1].sWord,-1))//Exist and update its frequncy as a POS value
pWordItems[j+nStartPos-1].dValue=LOG_MAX_FRQUENCE-log((double)dictCore.GetFrequency(pWordItems[j+nStartPos-1].sWord,m_nBestTag[j])+1);
j+=1;
}
break;
case TT_PERSON://Person recognition
/*clock_t lStart,lEnd;
lStart=clock();
*/
SplitPersonPOS(dictUnknown);
//lEnd=clock();
//printf("SplitPersonPOS=%f\n",(double)(lEnd-lStart)*1000/CLOCKS_PER_SEC);
//Spit Persons POS
//lStart=clock();
PersonRecognize(dictUnknown);
//lEnd=clock();
//printf("PersonRecognize=%f\n",(double)(lEnd-lStart)/CLOCKS_PER_SEC);
//Person Recognition with the person recognition dictionary
break;
case TT_PLACE://Place name recognition
PlaceRecognize(dictCore,dictUnknown);
break;
case TT_TRANS://Transliteration
TransRecognize(dictCore,dictUnknown);
break;
default:
break;
}
Reset();
}
return true;
}
bool CResult::ChineseNameSplit(char *sPersonName, char *sSurname, char *sSurname2, char *sGivenName, CDictionary &personDict)
{
int nSurNameLen=4,nLen=strlen(sPersonName),nFreq,i=0,nCharType,nFreqGiven;
char sTemp[3];
if(nLen<3||nLen>8)//Not a traditional Chinese person name
return false;
while(i<nLen)//No Including non-CHinese char
{
nCharType=charType((unsigned char*)sPersonName+i);
if(nCharType!=CT_CHINESE&&nCharType!=CT_OTHER)
return false;
i+=2;
}
sSurname2[0]=0;//init
strncpy(sSurname,sPersonName,nSurNameLen);
sSurname[nSurNameLen]=0;
if(!personDict.IsExist(sSurname,1))
{
nSurNameLen=2;
sSurname[nSurNameLen]=0;
if(!personDict.IsExist(sSurname,1))
{
nSurNameLen=0;
sSurname[nSurNameLen]=0;
}
}
strcpy(sGivenName,sPersonName+nSurNameLen);
if(nLen>6)
{
strncpy(sTemp,sPersonName+nSurNameLen,2);
sTemp[2]=0;//Get the second possible surname
if(personDict.IsExist(sTemp,1))
{//Hongkong women's name: Surname+surname+given name
strcpy(sSurname2,sTemp);
strcpy(sGivenName,sPersonName+nSurNameLen+2);
}
}
nFreq=personDict.GetFrequency(sSurname,1);
strncpy(sTemp,sGivenName,2);
sTemp[2]=0;
nFreqGiven=personDict.GetFrequency(sTemp,2);
if(nSurNameLen!=4&&((nSurNameLen==0&&nLen>4)||strlen(sGivenName)>4||(GetForeignCharCount(sPersonName)>=3&&nFreq<personDict.GetFrequency("张",1)/40&&nFreqGiven<personDict.GetFrequency("华",2)/20)||(nFreq<10&&GetForeignCharCount(sGivenName)==(nLen-nSurNameLen)/2)))
return false;
if(nLen==4&&m_uPerson.IsGivenName(sPersonName))
{//Single Surname+given name
return false;
}
return true;
}
int main(int argc, char *argv[])
{
SetConsoleOutputCP(1251);
SetConsoleCP(1251);
if (argc != 1)
{
cout << "The command has no additional parameters" << endl;
return 0;
}
string englishWord;
CDictionary dictionary;
CTranslator translator(dictionary);
while (getline(cin, englishWord) && englishWord != EXIT_LINE)
{
if (!englishWord.empty())
{
ConvertToLowercase(englishWord);
translator.DoDialogWithUser(englishWord);
}
}
string answer;
if (!dictionary.IsNewWordsListEmpty())
{
cout << "Do you want to save new words? YES/NO" << endl;
while (getline(cin, answer))
{
if (answer == "YES")
{
dictionary.DictionarySave();
break;
}
else if (answer == "NO")
{
break;
}
else
{
cout << "Try again" << endl;
}
}
}
return 0;
}
ELEMENT_TYPE CSpan::ComputePossibility(int nStartPos,int nLength,CDictionary &dict)
{
ELEMENT_TYPE dRetValue=0,dPOSPoss;
//dPOSPoss: the possibility of a POS appears
//dContextPoss: The possibility of context POS appears
int nFreq;
for(int i=nStartPos;i<nStartPos+nLength;i++)
{
nFreq=dict.GetFrequency(m_sWords[i],m_nBestTag[i]);
//nFreq is word being the POS
dPOSPoss=log((double)(m_context.GetFrequency(0,m_nBestTag[i])+1))-log((double)(nFreq+1));
dRetValue+=dPOSPoss;
/* if(i<nStartPos+nLength-1)
{
dContextPoss=log((double)(m_context.GetContextPossibility(0,m_nBestTag[i],m_nBestTag[i+1])+1));
dRetValue+=dPOSPoss-dContextPoss;
}
*/ }
return dRetValue;
}
int main(int argc, char *argv[])
{
SetConsoleOutputCP(1251);
SetConsoleCP(1251);
if (argc != 2)
{
cout << "Not enough parameters. The correct command line format:\ndictionary.exe <file name>" << "\n";
return 1;
}
else
{
ifstream inputFile(argv[1]);
string inputWord;
CDictionary dictionary;
if (inputFile.is_open())
{
dictionary.FillDictionary(inputFile);
}
cout << "Для перевода введите слово на английском. Для выхода введите '...'\n";
ofstream outputFile;
outputFile.open(argv[1], ios::app);
getline(cin, inputWord);
while (inputWord != "...")
{
if (dictionary.IsKnowWord(inputWord))
{
dictionary.PrintTranslation(inputWord);
}
else if (!inputWord.empty())
{
dictionary.SaveTranslationForNewWordOnUserDemand(inputWord);
}
getline(cin, inputWord);
}
dictionary.SaveNewWordsOnUserDemand(outputFile);
}
return 0;
}
int CSpan::GetFrom(PWORD_RESULT pWordItems,int nIndex,CDictionary &dictCore, CDictionary &dictUnknown)
{
int nCount,aPOS[MAX_POS_PER_WORD],aFreq[MAX_POS_PER_WORD];
int nFreq=0,j,nRetPos=0,nWordsIndex=0;
bool bSplit=false;//Need to split in Transliteration recognition
int i=1;
nWordsIndex=i+nIndex-1;
for(;i<MAX_WORDS_PER_SENTENCE&&pWordItems[nWordsIndex].sWord[0]!=0;i++)
{
if(m_tagType==TT_NORMAL||!dictUnknown.IsExist(pWordItems[nWordsIndex].sWord,44))
{
strcpy(m_sWords[i],pWordItems[nWordsIndex].sWord);//store current word
m_nWordPosition[i+1]=m_nWordPosition[i]+strlen(m_sWords[i]);
}
else
{
if(!bSplit)
{
strncpy(m_sWords[i],pWordItems[nWordsIndex].sWord,2);//store current word
m_sWords[i][2]=0;
bSplit=true;
}
else
{
unsigned int nLen=strlen(pWordItems[nWordsIndex].sWord+2);
strncpy(m_sWords[i],pWordItems[nWordsIndex].sWord+2,nLen);//store current word
m_sWords[i][nLen]=0;
bSplit=false;
}
m_nWordPosition[i+1]=m_nWordPosition[i]+strlen(m_sWords[i]);
}
//Record the position of current word
m_nStartPos=m_nWordPosition[i+1];
//Move the Start POS to the ending
if(m_tagType!=TT_NORMAL)
{
//Get the POSs from the unknown recognition dictionary
dictUnknown.GetHandle(m_sWords[i],&nCount,aPOS,aFreq);
for(j=0;j<nCount;j++)
{//Get the POS set of sCurWord in the unknown dictionary
m_nTags[i][j]=aPOS[j];
m_dFrequency[i][j]=-log((double)(1+aFreq[j]))+log((double)(m_context.GetFrequency(0,aPOS[j])+1));
}
//Get the POS set of sCurWord in the core dictionary
//We ignore the POS in the core dictionary and recognize them as other (0).
//We add their frequency to get the possibility as POS 0
dictCore.GetHandle(m_sWords[i],&nCount,aPOS,aFreq);
nFreq=0;
for(int k=0;k<nCount;k++)
{
nFreq+=aFreq[k];
}
if(nCount>0)
{
m_nTags[i][j]=0;
//m_dFrequency[i][j]=(double)(1+nFreq)/(double)(m_context.GetFrequency(0,0)+1);
m_dFrequency[i][j]=-log((double)(1+nFreq))+log((double)(m_context.GetFrequency(0,0)+1));
j++;
}
}
else//For normal POS tagging
{
j=0;
//Get the POSs from the unknown recognition dictionary
if(pWordItems[nWordsIndex].nHandle>0)
{//The word has is only one POS value
//We have record its POS and nFrequncy in the items.
m_nTags[i][j]=pWordItems[nWordsIndex].nHandle;
m_dFrequency[i][j]=pWordItems[nWordsIndex].dValue-LOG_MAX_FRQUENCE+log((double)(m_context.GetFrequency(0,m_nTags[i][j])+1));
if(m_dFrequency[i][j]<0)//Not permit the value less than 0
m_dFrequency[i][j]=0;
j++;
}
else
{//The word has multiple POSs, we should retrieve the information from Core Dictionary
if(pWordItems[nWordsIndex].nHandle<0)
{//The word has is only one POS value
//We have record its POS and nFrequncy in the items.
if(pWordItems[nWordsIndex].nHandle==-'t'*256-'t')//tt
{
char sWordOrg[100],sPostfix[10];
double dRatio=0.6925;//The ratio which transliteration as a person name
PostfixSplit(pWordItems[nWordsIndex].sWord,sWordOrg,sPostfix);
if(sPostfix[0]!=0)
dRatio=0.01;
m_nTags[i][j]='n'*256+'r';
m_dFrequency[i][j]=-log(dRatio)+pWordItems[nWordsIndex].dValue;
//m_dFrequency[i][j]=log(dRatio)+pWordItems[nWordsIndex].dValue-log(m_context.GetFrequency(0,m_nTags[i][j]))+log(MAX_FREQUENCE);
//P(W|R)=P(WRT)/P(RT)=P(R)*P(W|T)/P(R|T)
j++;
m_nTags[i][j]='n'*256+'s';
m_dFrequency[i][j]=-log(1-dRatio)+pWordItems[nWordsIndex].dValue;
//m_dFrequency[i][j]=log(1-dRatio)+pWordItems[nWordsIndex].dValue-log(m_context.GetFrequency(0,m_nTags[i][j]))+log(MAX_FREQUENCE);
j++;
}
else//Unknown words such as Chinese person name or place name
{
m_nTags[i][j]=-pWordItems[nWordsIndex].nHandle;
// m_dFrequency[i][j++]=(double)(1+pWordItems[nWordsIndex].nFrequency)/(double)(m_context.GetFrequency(0,aPOS[j])+1);
m_dFrequency[i][j++]=pWordItems[nWordsIndex].dValue;
}
}
dictCore.GetHandle(m_sWords[i],&nCount,aPOS,aFreq);
for(;j<nCount;j++)
{//Get the POS set of sCurWord in the unknown dictionary
m_nTags[i][j]=aPOS[j];
m_dFrequency[i][j]=-log((double)1+aFreq[j])+log((double)m_context.GetFrequency(0,m_nTags[i][j])+1);
}
}
}
if(j==0)
{//We donot know the POS, so we have to guess them according lexical knowledge
GuessPOS(i,&j);//Guess the POS of current word
}
m_nTags[i][j]=-1;//Set the ending POS
if(j==1)//No ambuguity
{//No ambuguity, so we can break from the loop
i++;
m_sWords[i][0]=0;
break;
}
if(!bSplit)
{nWordsIndex++;}
}
if(pWordItems[nWordsIndex].sWord[0]==0)
nRetPos=-1;//Reaching ending
if(m_nTags[i-1][1]!=-1)//||m_sWords[i][0]==0
{//Set end for words like "张/华/平"
if(m_tagType!=TT_NORMAL)
m_nTags[i][0]=101;
else
m_nTags[i][0]=1;
m_dFrequency[i][0]=0;
m_sWords[i][0]=0;//Set virtual ending
m_nTags[i++][1]=-1;
}
m_nCurLength=i;//The current word count
if(nRetPos!=-1)
return nWordsIndex+1;//Next start position
return -1;//Reaching ending
}
bool CSpan::PersonRecognize(CDictionary &personDict)
{
char sPOS[MAX_WORDS_PER_SENTENCE]="z",sPersonName[100];
//0 1 2 3 4 5
char sPatterns[][5]={ "BBCD","BBC","BBE","BBZ","BCD","BEE","BE",
"BG", "BXD","BZ", "CDCD","CD","EE",
"FB", "Y","XD",""};
double dFactor[]={0.0011,0.0011,0.0011,0.0011,0.7614,0.0011,0.2055,
0.0160,0.0011,0.0011,0,0.0160,0.0011,
0.0160,0.0011,0.0011,0 };
//About parameter:
/*
Given Name: 486 0.0160
Surname+postfix:484 0.0160
m_lPerson2Num:6265 0.2055
m_lPerson3Num: 23184 0.7614
m_lPerson4Num:32 0.0011
*/
//The person recognition patterns set
//BBCD:姓+姓+名1+名2;
//BBE: 姓+姓+单名;
//BBZ: 姓+姓+双名成词;
//BCD: 姓+名1+名2;
//BE: 姓+单名;
//BEE: 姓+单名+单名;韩磊磊
//BG: 姓+后缀
//BXD: 姓+姓双名首字成词+双名末字
//BZ: 姓+双名成词;
//B: 姓
//CD: 名1+名2;
//EE: 单名+单名;
//FB: 前缀+姓
//XD: 姓双名首字成词+双名末字
//Y: 姓单名成词
int nPatternLen[]={4,3,3,3,3,3,2,2,3,2,4,2,2,2,1,2,0};
int i;
for(i=1;m_nBestTag[i]>-1;i++)//Convert to string from POS
sPOS[i]=m_nBestTag[i]+'A';
sPOS[i]=0;
int j=1,k,nPos;//Find the proper pattern from the first POS
int nLittleFreqCount;//Counter for the person name role with little frequecy
bool bMatched=false;
while(j<i)
{
bMatched=false;
for(k=0;!bMatched&&nPatternLen[k]>0;k++)
{
if(strncmp(sPatterns[k],sPOS+j,nPatternLen[k])==0&&strcmp(m_sWords[j-1],"·")!=0&&strcmp(m_sWords[j+nPatternLen[k]],"·")!=0)
{//Find the proper pattern k
if(strcmp(sPatterns[k],"FB")==0&&(sPOS[j+2]=='E'||sPOS[j+2]=='C'||sPOS[j+2]=='G'))
{//Rule 1 for exclusion:前缀+姓+名1(名2): 规则(前缀+姓)失效；
continue;
}
/* if((strcmp(sPatterns[k],"BEE")==0||strcmp(sPatterns[k],"EE")==0)&&strcmp(m_sWords[j+nPatternLen[k]-1],m_sWords[j+nPatternLen[k]-2])!=0)
{//Rule 2 for exclusion:姓+单名+单名:单名+单名 若EE对应的字不同，规则失效.如：韩磊磊
continue;
}
if(strcmp(sPatterns[k],"B")==0&&m_nBestTag[j+1]!=12)
{//Rule 3 for exclusion: 若姓后不是后缀，规则失效.如：江主席、刘大娘
continue;
}
*/ //Get the possible name
nPos=j;//Record the person position in the tag sequence
sPersonName[0]=0;
nLittleFreqCount=0;//Record the number of role with little frequency
while(nPos<j+nPatternLen[k])
{//Get the possible person name
//
if(m_nBestTag[nPos]<4&&personDict.GetFrequency(m_sWords[nPos],m_nBestTag[nPos])<LITTLE_FREQUENCY)
nLittleFreqCount++;//The counter increase
strcat(sPersonName,m_sWords[nPos]);
nPos+=1;
}
if(IsAllForeign(sPersonName)&&personDict.GetFrequency(m_sWords[j],1)<LITTLE_FREQUENCY)
{//Exclusion foreign name
//Rule 2 for exclusion:若均为外国人名用字 规则(名1+名2)失效
j+=nPatternLen[k]-1;
continue;
}
if(strcmp(sPatterns[k],"CDCD")==0)
{//Rule for exclusion
//规则(名1+名2+名1+名2)本身是排除规则:女高音歌唱家迪里拜尔演唱
//Rule 3 for exclusion:含外国人名用字 规则适用
//否则，排除规则失效:黑妞白妞姐俩拔了头筹。
if(GetForeignCharCount(sPersonName)>0)
j+=nPatternLen[k]-1;
continue;
}
if(strcmp(sPatterns[k],"CD")==0&&IsAllForeign(sPersonName))
{//
j+=nPatternLen[k]-1;
continue;
}
if(nLittleFreqCount==nPatternLen[k]||nLittleFreqCount==3)
//马哈蒂尔;小扎耶德与他的中国阿姨胡彩玲受华黎明大使之邀，
//The all roles appear with two lower frequecy,we will ignore them
continue;
m_nUnknownWords[m_nUnknownIndex][0]=m_nWordPosition[j];
m_nUnknownWords[m_nUnknownIndex][1]=m_nWordPosition[j+nPatternLen[k]];
m_dWordsPossibility[m_nUnknownIndex]=log(dFactor[k])+ComputePossibility(j,nPatternLen[k],personDict);
//Mutiply the factor
m_nUnknownIndex+=1;
j+=nPatternLen[k];
bMatched=true;
}
}
if(!bMatched)//Not matched, add j by 1
j+=1;
}
return true;
}
int main(int argc, char **argv)
{
if (argc != 4)
PrintUsage();
if ( !strcmp (argv[1], "-h")
|| !strcmp (argv[1], "-help")
|| !strcmp (argv[1], "/h")
|| !strcmp (argv[1], "/help")
)
PrintUsage();
string Action = argv[1];
if ( (Action != "ToTxt")
&& (Action != "FromTxt")
)
PrintUsage();
string FileName = argv[2];
CDictionary Dict;
if (Action == "FromTxt")
{
if (access (FileName.c_str(), 04) != 0)
{
fprintf (stderr, "Cannot read %s\n",FileName.c_str());
return 1;
};
if (!Dict.LoadOnlyConstants(argv[3]))
{
fprintf (stderr, "Cannot load an empty dictionary from %s\n",argv[3]);
return 1;
};
Dict.m_bShouldSaveComments = true;
string Messages;
bool bResult = Dict.ImportFromText(FileName,false, iceSkip,1, Messages);
fprintf (stderr, "%s", Messages.c_str() );
if (bResult)
if (Dict.Save())
return 0;
return 1;
}
else
{
if (!Dict.Load(argv[3]) || !Dict.ReadUnitComments())
{
fprintf (stderr, "Cannot load dictionary from %s\n",argv[3]);
return 1;
};
FILE * fp = fopen (FileName.c_str(),"wb");
if (!fp)
{
fprintf (stderr, "Cannot write to %s\n",FileName.c_str());
return 1;
};
CTempArticle A;
A.m_pRoss = &Dict;
for (WORD i = 0; i < Dict.m_Units.size(); i++)
{
fprintf (fp,"============\r\n");
fprintf (fp,"%s", Dict.GetUnitTextHeader(i).c_str());
try
{
A.ReadFromDictionary(i, false, true);
if (!A.ArticleToText())
{
fprintf (fp,"Error! Cannot get the entry No %i\r\n", i);
return 1;
};
fprintf (fp,"%s",A.GetArticleStr().c_str());
}
catch (...)
{
fprintf (fp,"Error! Cannot get the entry No %i\r\n", i);
return 1;
}
};
fclose(fp);
return 0;
};
}
void InjectWord(unsigned w, unsigned val) {
dictionary.AddWord(w, val, false);
}
bool CSpan::SplitPersonPOS(CDictionary &unlistDict)
{//Split the word with POS 21 and 22
int i=m_nCurLength-1,j;
unsigned int nLenWord,nLenPart;
char sFirstPart[50],sLastPart[50];
int nFirstPOS,nLastPOS;
for(;i>0;i--)
{
if(m_nBestTag[i]==21||m_nBestTag[i]==22)
{//Find the POS which need to split
for(j=m_nCurLength-1;j>i;j--)
{//Move the POS and words
strcpy(m_sWords[j+1],m_sWords[j]);
m_nBestTag[j+1]=m_nBestTag[j];
m_nWordPosition[j+1]=m_nWordPosition[j];
}
m_nCurLength+=1;//The length increment
//Generate new segment words and POS
if(m_nBestTag[i]==21)
{//Combination by Previous and first component
nLenWord=strlen(m_sWords[i]);
if(nLenWord>4)//Get first component
{
strcpy(sLastPart,m_sWords[i]+nLenWord-4);
if(!unlistDict.IsExist(sLastPart,-1))
strcpy(sLastPart,m_sWords[i]+nLenWord-2);
}
else
{
strcpy(sLastPart,m_sWords[i]+nLenWord-2);
}
nLenPart=strlen(sLastPart);
if(nLenPart<nLenWord)
{//Get first part
strncpy(sFirstPart,m_sWords[i],nLenWord-nLenPart);
sFirstPart[nLenWord-nLenPart]=0;
}
else
{
strncpy(sFirstPart,m_sWords[i],nLenWord-2);
sFirstPart[nLenWord-2]=0;
strncpy(sLastPart,m_sWords[i]+nLenWord-2,2);
sLastPart[2]=0;
}
nFirstPOS=11;
nLastPOS=1;
}
else
{//Combination by Next word and last component
nLenWord=strlen(m_sWords[i]);
if(nLenWord>4)//Get last component
{
strncpy(sFirstPart,m_sWords[i],4);
sFirstPart[4]=0;
if(!unlistDict.IsExist(sFirstPart,-1))
sFirstPart[2]=0;
}
else
{
strncpy(sFirstPart,m_sWords[i],2);
sFirstPart[2]=0;
}
nLenPart=strlen(sFirstPart);
if(nLenPart<nLenWord)
{//Get first part
strncpy(sLastPart,m_sWords[i]+nLenPart,nLenWord-nLenPart);
sLastPart[nLenWord-nLenPart]=0;
}
else
{
strncpy(sFirstPart,m_sWords[i],2);
sFirstPart[2]=0;
strncpy(sLastPart,m_sWords[i]+2,nLenWord-2);
sLastPart[nLenWord-2]=0;
}
if(unlistDict.IsExist(sFirstPart,1)&&m_nBestTag[i-1]==5)
//小陈说：
nFirstPOS=1;
else if(unlistDict.IsExist(m_sWords[i-1],1)&&!unlistDict.IsExist(m_sWords[i-2],1))
nFirstPOS=4;
else
nFirstPOS=3;
nLastPOS=12;
}
strcpy(m_sWords[i],sFirstPart);
m_nBestTag[i]=nFirstPOS;
strcpy(m_sWords[i+1],sLastPart);
m_nBestTag[i+1]=nLastPOS;
m_nWordPosition[i+1]=m_nWordPosition[i]+strlen(sFirstPart);
}
}
return true;
}
Dictionary_()
{
ss << "cat" << endl << "кошка" << endl << "dog" << endl << "собака";
dictionary.LoadDictionary(ss);
}
string TranslateIn8Power(int Num)
{
return Translate(Num,8)+Comments.GetTranslate("Ru comment about hex system");
}
void BeginDictionaryTransaction() {
dictionary.BeginTransaction();
}
void CViewport::LoadDictionary(void)
{
CSV::CSVDocument doc;
CSV::CSVDocument::row_index_type row_count;
//Parse from the document
try
{
row_count = doc.load_file("captionmod/dictionary.csv");
}
catch(std::exception &err)
{
Sys_ErrorEx("%s\n%s", "LoadDictionary: ", err.what());
}
if(row_count < 2)
return;
IScheme *ischeme = scheme()->GetIScheme(GetScheme());
if(!ischeme)
return;
Color defaultColor = ischeme->GetColor("BaseText", Color(255, 255, 255, 200));
//Initialize the dictionary hashtable
m_StringsHashTable.SetSize(2048);
for (int i = 0; i < m_StringsHashTable.Count(); i++)
m_StringsHashTable[i].next = NULL;
EmptyDictionaryHash();
int nRowCount = row_count;
//parse the dictionary line by line...
for (int i = 1;i < nRowCount; ++i)
{
CSV::CSVDocument::row_type row = doc.get_row(i);
if(row.size() < 1)
continue;
const char *title = row[0].c_str();
if(!title || !title[0])
continue;
CDictionary *Dict = new CDictionary;
Dict->Load(row, defaultColor, ischeme);
m_Dictionary.AddToTail(Dict);
AddDictionaryHash(Dict, Dict->m_szTitle);
}
//Link the dictionaries
for(int i = 0; i < m_Dictionary.Count(); ++i)
{
CDictionary *Dict = m_Dictionary[i];
if(Dict->m_szNext[0])
{
Dict->m_pNext = FindDictionary(Dict->m_szNext);
}
}
}
void HandleCreate(const CDictionary& dict)
{
super::HandleCreate(dict);
CRGBA rgbaTint(255,255,255,255);
dict.GetRGBA("tint", &rgbaTint);
for ( uint32 iButtonImage = 0 ; iButtonImage < 9 ; ++iButtonImage )
{
m_apImages[iButtonImage]->SetShader(GetTheme()->GetButtonImage(iButtonImage));
m_apImages[iButtonImage]->SetTint(rgbaTint);
}
if ( dict.Exists("font") )
{
m_pText->SetFont(dict.GetString("font"));
}
else
{
m_pText->SetFont(GetTheme()->GetButtonTextFont());
}
if ( dict.Exists("text") )
{
m_pText->SetText(dict.GetString("text").c_str());
}
if ( dict.Exists("text_shadow") )
{
bool bShadow = dict.GetBool("text_shadow");
int nStyle = m_pText->GetStyle();
m_pText->SetStyle(IText::Style(bShadow ? (nStyle | IText::eStyleShadowed) : (nStyle & ~IText::eStyleShadowed)));
}
if ( dict.Exists("text_tint") )
{
m_pText->SetTint(dict.GetRGBA("text_tint"));
}
if ( dict.Exists("onpress") )
{
m_sOnPress = dict.GetString("onpress");
}
if ( dict.Exists("onunpress") )
{
m_sOnUnpress = dict.GetString("onunpress");
}
}
void BootstrapDB() {
dictionary.ClearAll();
markov.ClearAll();
}
bool CSpan::TransRecognize(CDictionary &dictCore,CDictionary &transDict)
{
char sPOS[MAX_WORDS_PER_SENTENCE]="Z";
int nStart=1,nEnd=1,i=1;
while(m_nBestTag[i]>-1)
{
if(m_nBestTag[i]==1||m_nBestTag[i]==11||m_nBestTag[i]==21)//1,11,21 Trigger the recognition
{
nStart=i;
nEnd=nStart+1;
while(m_nBestTag[nEnd]==m_nBestTag[nStart])//1,11,21
nEnd++;
while(m_nBestTag[nEnd]==m_nBestTag[nStart]+1)//2,12,22
nEnd++;
while(m_nBestTag[nEnd]==m_nBestTag[nStart]+2)//3,13,23
nEnd++;
while(m_nBestTag[nEnd]==30)//3,13,23
nEnd++;
}
else if(m_nBestTag[i]==2||m_nBestTag[i]==12||m_nBestTag[i]==22)//1,11,21 Trigger the recognition
{
nStart=i;
nEnd=nStart+1;
while(m_nBestTag[nEnd]==m_nBestTag[nStart])//2,12,22
nEnd++;
while(m_nBestTag[nEnd]==m_nBestTag[nStart]+1)//2,12,22
nEnd++;
while(m_nBestTag[nEnd]==30)//3,13,23
nEnd++;
}
if(nEnd>nStart&&!IsAllNum((unsigned char *)m_sWords[nStart])&&(nEnd>nStart+2||(nEnd==nStart+2&&(m_nBestTag[nEnd-1]!=30||strlen(m_sWords[nStart])>2))||(nEnd==nStart+1&&strlen(m_sWords[nStart])>2&&!dictCore.IsExist(m_sWords[nStart],-1))))
{
m_nUnknownWords[m_nUnknownIndex][0]=m_nWordPosition[nStart];
m_nUnknownWords[m_nUnknownIndex][1]=m_nWordPosition[nEnd];
m_dWordsPossibility[m_nUnknownIndex++]=ComputePossibility(nStart,nEnd-nStart+1,transDict);
nStart=nEnd;
}
if(i<nEnd)
i=nEnd;
else
i=i+1;
}
return true;
}
string TranslateIn10Power(int Num)
{
return Translate(Num,10)+Comments.GetTranslate("Ru comment about dec system");
}
bool CSegGraph::GenerateWordNet(char *sSentence,CDictionary &dictCore,bool bOriginalFreq)
{
//Gernerate the word net from the sLine, that's list all the possible word
unsigned int i=0,j,nLen=strlen(sSentence);
char sWord[WORD_MAXLENGTH]="",sTempWord[WORD_MAXLENGTH]="",sWordMatch[WORD_MAXLENGTH];
int nWordIndex=0,nHandleTemp,k,nPOS;
int nMatchFreq[20],nMatchHandle[20],nTotalFreq,nMatchCount;
double dValue=0;
m_nAtomCount=0;
m_segGraph.SetEmpty();//Set segmentation graph empty
AtomSegment(sSentence);
//Atomic Segmentation
for(i=0;i<m_nAtomCount;i++)//Init the cost array
{
if(m_nAtomPOS[i]==CT_CHINESE)//The atom is a Chinese Char
{
if(!bOriginalFreq)//Not original frequency
m_segGraph.SetElement(i,i+1,log(MAX_FREQUENCE),0);//init the link with the maximum value
else
m_segGraph.SetElement(i,i+1,0,0,m_sAtom[i]);//init the link with the maximum value
}
else//Other atom
{
strcpy(sWord,m_sAtom[i]);//init the word
dValue=MAX_FREQUENCE;
switch(m_nAtomPOS[i])
{
case CT_INDEX:
case CT_NUM:
nPOS=-27904;//'m'*256
strcpy(sWord,"未##数");
dValue=0;
break;
case CT_DELIMITER:
nPOS=30464;//'w'*256;
break;
case CT_LETTER:
nPOS=-'n'*256-'x';//
dValue=0;
strcpy(sWord,"未##串");
break;
case CT_SINGLE://12021-2129-3121
if(GetCharCount("+-1234567890",m_sAtom[i])==(int)strlen(m_sAtom[i]))
{
nPOS=-27904;//'m'*256
strcpy(sWord,"未##数");
}
else
{
nPOS=-'n'*256-'x';//
strcpy(sWord,"未##串");
}
dValue=0;
break;
default:
nPOS=m_nAtomPOS[i];//'?'*256;
break;
}
if(!bOriginalFreq)//Not original frequency
m_segGraph.SetElement(i,i+1,0,nPOS);//init the link with minimum
else
m_segGraph.SetElement(i,i+1,dValue,nPOS,sWord);//init the link with minimum
}
}
i=0;
while(i<m_nAtomCount)//All the word
{
strcpy(sWord,m_sAtom[i]);//Get the current atom
j=i+1;
if(strcmp(sWord,"月")==0&&strcmp(m_sAtom[i+1],"份")==0)//Don't split 月份
j+=1;
while(j<=m_nAtomCount&&dictCore.GetMaxMatch(sWord,sWordMatch,&nHandleTemp))
{//Add a condition to control the end of string
//retrieve the dictionary with the word
if(strcmp(sWordMatch,sWord)==0)//find the current word
{
nTotalFreq=0;
dictCore.GetHandle(sWord,&nMatchCount,nMatchHandle,nMatchFreq);
for(k=0;k<nMatchCount;k++)//Add the frequency
{
nTotalFreq+=nMatchFreq[k];
}
//Adding a rule to exclude some words to be formed.
if(strlen(sWord)==4&&i>=1&&(IsAllNum((unsigned char *)m_sAtom[i-1])||IsAllChineseNum(m_sAtom[i-1]))&&(strncmp(sWord,"年",2)==0||strncmp(sWord,"月",2)==0))
{//1年内、1999年末
if(CC_Find("末内中底前间初",sWord+2))
break;
}
if(nMatchCount==1)//The possible word has only one POS, store it
{
if(!bOriginalFreq)//Not original frequency
m_segGraph.SetElement(i,j,-log(nTotalFreq+1)+log(MAX_FREQUENCE),nMatchHandle[0]);
else
m_segGraph.SetElement(i,j,nTotalFreq,nMatchHandle[0],sWord);
}
else
{
if(!bOriginalFreq)//Not original frequency
m_segGraph.SetElement(i,j,-log(nTotalFreq+1)+log(MAX_FREQUENCE),0);
else
m_segGraph.SetElement(i,j,nTotalFreq,0,sWord);
}
}
strcat(sWord,m_sAtom[j++]);
}
i+=1;//Start from i++;
}
return true;
}
void EndDictionaryTransaction() {
dictionary.EndTransaction();
}