Exemplo n.º 1
0
        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();
        }
Exemplo n.º 2
0
        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);
        }
Exemplo n.º 3
0
		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();

		}
Exemplo n.º 4
0
        static string[] GetAllDefinitionTokens(Search se)
        {
            string rels = "";

            if (se.senses[0].senses != null)
            {
                foreach (SynSet ss in se.senses[0].senses)
                {
                    foreach (var ww in ss.words)
                    {
                        rels += " " + ww.word;
                    }
                    rels += ss.defn;
                }
            }

            string[] toks = Tokenize.Partition(rels);
            return(toks);
        }
Exemplo n.º 5
0
        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;	
		}