private void MyInit()
{
ISimilarity editdistance = new Leven();
getSimilarity = new Similarity(editdistance.GetSimilarity);
//ISimilarity lexical=new LexicalSimilarity() ;
//getSimilarity=new Similarity(lexical.GetSimilarity) ;
var tokeniser = new Tokeniser();
_leftTokens = tokeniser.Partition(_lString);
_rightTokens = tokeniser.Partition(_rString);
if (_leftTokens.Length > _rightTokens.Length)
{
string[] tmp = _leftTokens;
_leftTokens = _rightTokens;
_rightTokens = tmp;
string s = _lString; _lString = _rString; _rString = s;
}
leftLen = _leftTokens.Length - 1;
rightLen = _rightTokens.Length - 1;
this.Initialize();
}
public MatchsMaker MyInit()
{
ISimilarity editdistance = new Leven();
getSimilarity = new Similarity(editdistance.GetSimilarity);
//ISimilarity lexical=new LexicalSimilarity() ;
//getSimilarity=new Similarity(lexical.GetSimilarity) ;
Tokeniser tokeniser = new Tokeniser();
_leftTokens = tokeniser.Partition(_lString);
_rightTokens = tokeniser.Partition(_rString);
if (_leftTokens.Length > _rightTokens.Length)
{
string[] tmp = _leftTokens;
_leftTokens = _rightTokens;
_rightTokens = tmp;
string s = _lString; _lString = _rString; _rString = s;
}
leftLen = _leftTokens.Length - 1;
rightLen = _rightTokens.Length - 1;
Initialize();
return(this);
}
private void MyInit()
{
ISimilarity editdistance=new Leven() ;
getSimilarity=new Similarity(editdistance.GetSimilarity) ;
//ISimilarity lexical=new LexicalSimilarity() ;
//getSimilarity=new Similarity(lexical.GetSimilarity) ;
Tokeniser tokeniser=new Tokeniser() ;
_leftTokens=tokeniser.Partition(_lString);
_rightTokens=tokeniser.Partition(_rString);
if (_leftTokens.Length > _rightTokens.Length)
{
string[] tmp=_leftTokens;
_leftTokens=_rightTokens;
_rightTokens=tmp;
string s=_lString; _lString=_rString; _rString=s;
}
leftLen=_leftTokens.Length - 1 ;
rightLen=_rightTokens.Length - 1;
Initialize();
}
public float GetScore(string string1, string string2)
{
Tokeniser tok = new Tokeniser();
tok.UseStemming = false;
_source = tok.Partition(string1);
_target = tok.Partition(string2);
if (_source.Length == 0 || _target.Length == 0)
{
return(0F);
}
float[][] simMatrix = GetSimilarityMatrix(_source, _target);
HeuristicMatcher match = new HeuristicMatcher();
//float score = HeuristicMatcher.ComputeSetSimilarity(simMatrix, 2, 0.3F);
float score = HeuristicMatcher.ComputeSetSimilarity(simMatrix, 1);
return(score);
}
public float GetScore(string string1, string string2)
{
Tokeniser tok=new Tokeniser() ;
tok.UseStemming = false;
_source=tok.Partition(string1) ;
_target=tok.Partition(string2) ;
if (_source.Length == 0 || _target.Length == 0 )
return 0F;
float[][] simMatrix = GetSimilarityMatrix(_source, _target);
HeuristicMatcher match=new HeuristicMatcher() ;
//float score = HeuristicMatcher.ComputeSetSimilarity(simMatrix, 2, 0.3F);
float score = HeuristicMatcher.ComputeSetSimilarity(simMatrix, 1);
return score;
}
