//Unknown word recognition
//pWordSegResult:word Segmentation result;
//graphOptimum: The optimized segmentation graph
//graphSeg: The original segmentation graph
public bool Recognition(WordResult[] pWordSegResult, RowFirstDynamicArray <ChainContent> graphOptimum,
List <AtomNode> atomSegment, WordDictionary dictCore)
{
ChainItem <ChainContent> item;
int nStartPos = 0, j = 0, nAtomStart, nAtomEnd, nPOSOriginal;
double dValue;
m_roleTag.POSTagging(pWordSegResult, dictCore, m_dict);
//Tag the segmentation with unknown recognition roles according the core dictionary and unknown recognition dictionary
for (int i = 0; i < m_roleTag.m_nUnknownWordsCount; i++)
{
while (j < atomSegment.Count && nStartPos < m_roleTag.m_nUnknownWords[i, 0])
{
nStartPos += atomSegment[j++].sWord.Length;
}
nAtomStart = j;
while (j < atomSegment.Count && nStartPos < m_roleTag.m_nUnknownWords[i, 1])
{
nStartPos += atomSegment[j++].sWord.Length;
}
nAtomEnd = j;
if (nAtomStart < nAtomEnd)
{
item = graphOptimum.GetElement(nAtomStart, nAtomEnd);
if (item != null)
{
dValue = item.Content.eWeight;
nPOSOriginal = item.Content.nPOS;
}
else
{
dValue = Predefine.INFINITE_VALUE;
}
if (dValue > m_roleTag.m_dWordsPossibility[i])
{
//Set the element with less frequency
graphOptimum.SetElement(nAtomStart, nAtomEnd, new ChainContent(m_roleTag.m_dWordsPossibility[i], m_nPOS, m_sUnknownFlags));
}
}
}
return(true);
}
public List <WordResult[]> Segment(string sentence, int nKind)
{
OnBeginSegment(sentence);
m_pNewSentence = Predefine.SENTENCE_BEGIN + sentence + Predefine.SENTENCE_END;
int nResultCount = m_Seg.BiSegment(m_pNewSentence, m_dSmoothingPara, nKind);
for (int i = 0; i < nResultCount; i++)
{
if (this.PersonRecognition)
{
m_uPerson.Recognition(m_Seg.m_pWordSeg[i], m_Seg.m_graphOptimum, m_Seg.atomSegment, m_dictCore);
}
if (this.TransPersonRecognition)
{
m_uTransPerson.Recognition(m_Seg.m_pWordSeg[i], m_Seg.m_graphOptimum, m_Seg.atomSegment, m_dictCore);
}
if (this.PlaceRecognition)
{
m_uPlace.Recognition(m_Seg.m_pWordSeg[i], m_Seg.m_graphOptimum, m_Seg.atomSegment, m_dictCore);
}
}
OnPersonAndPlaceRecognition(m_Seg.m_graphOptimum);
m_Seg.BiOptimumSegment(1, m_dSmoothingPara);
for (int i = 0; i < m_Seg.m_pWordSeg.Count; i++)
{
m_POSTagger.POSTagging(m_Seg.m_pWordSeg[i], m_dictCore, m_dictCore);
}
OnFinishSegment(m_Seg.m_pWordSeg);
return(m_Seg.m_pWordSeg);
}