Strabo.Core.TextRecognition.JaccardDistance.GetDistance C# (CSharp) Méthode

        public float GetDistance(String source, String target)
        {
            int sl = source.Length;
            int tl = target.Length;

            if (sl == 0 || tl == 0)
            {
                if (sl == tl)
                {
                    return 1;
                }
                else
                {
                    return 0;
                }
            }
            if (sl < n || tl < n)
                return 0;

            char[] sa = new char[sl + 2*n - 2];
            char[] ta = new char[tl + 2 * n - 2];

            for(int i=0;i<sa.Length;i++)
            {
                if (i < n - 1 || i>sl)
                    sa[i] = (char)0;//padding
                else
                    sa[i] = source[i - n + 1];
            }

            for (int i = 0; i < ta.Length; i++)
            {
                if (i < n - 1 || i > tl)
                    ta[i] = (char)0;//padding
                else
                    ta[i] = target[i - n + 1];
            }

            HashSet<string> sset = new HashSet<string>();
            HashSet<string> tset = new HashSet<string>();
            HashSet<string> allset = new HashSet<string>();

            for(int i=0;i<sa.Length-n+1;i++)
            {
                char[] qgram = new char[n];
                for (int j = 0; j < n; j++)
                    qgram[j] = sa[i + j];
                sset.Add(new string(qgram));
                allset.Add(new string(qgram));
            }
            for (int i = 0; i < ta.Length - n + 1; i++)
            {
                char[] qgram = new char[n];
                for (int j = 0; j < n; j++)
                    qgram[j] = ta[i + j];
                tset.Add(new string(qgram));
                allset.Add(new string(qgram));
            }

            int matches = 0;
            foreach(string qgram in allset)
            {
                if (sset.Contains(qgram) && tset.Contains(qgram))
                    matches++;
            }

            return (float)matches / (float)(allset.Count);
        }

        public static double findSimilarDictionaryWord(string word, double maxSimilarity, int index, List<string> equalMinDistanceDictWordList)
        {
            index = index - _minWordLength;
            word = word.ToLower();
            double NewSimilarity = 0;
            int WordLength = word.Length;
            if ((WordLength + index) < 0)
                return maxSimilarity;
            if ((WordLength + index) >= _IndexDictionary.Length)
                return maxSimilarity;
            if (_IndexDictionary[WordLength + index] == null)
                return maxSimilarity;

            for (int j = 0; j < _IndexDictionary[WordLength + index].Count; j++)
            {
                JaroWinklerDistance JaroDist = new JaroWinklerDistance();
                NGramDistance ng = new NGramDistance();
                JaccardDistance jd = new JaccardDistance();

                NewSimilarity = jd.GetDistance(word, _IndexDictionary[WordLength + index][j]);//(double)JaroDist.GetDistance(word, _IndexDictionary[WordLenght - 1 + index][j]);

                if (NewSimilarity > maxSimilarity)
                {
                    equalMinDistanceDictWordList.Clear();
                    equalMinDistanceDictWordList.Add(_IndexDictionary[WordLength + index][j]);
                    maxSimilarity = NewSimilarity;
                }
                else if (NewSimilarity == maxSimilarity)
                    equalMinDistanceDictWordList.Add(_IndexDictionary[WordLength + index][j]);
            }
            return maxSimilarity;
        }