/// <summary>
    /// Levenshtein Distance
    /// </summary>
    static class StringExt
    {
        /// <summary>
        /// 计算两个字符串的差异距离
        /// </summary>
        /// <param name="source">来源字符串</param>
        /// <param name="target">目标字符串</param>
        /// <returns>字符串差距</returns>
        public static int CalcDistance(this string source, string target)
        {
            int n = source.Length;
            int m = target.Length;
            if (m == 0) return n;
            if (n == 0) return m;
            var matrix = new int[n + 1, m + 1];
            for (int i = 1; i <= n; i++)
            {
                matrix[i, 0] = i;
            }
            for (int i = 1; i <= m; i++)
            {
                matrix[0, i] = i;
            }for (int i = 1; i <= n; i++)
            {
                var si = source[i - 1];
                for (int j = 1; j <= m; j++)
                {
                    var tj = target[j - 1];int cost;
                    if (si == tj)
                        cost = 0;
                    else
                        cost = 1;int above = matrix[i - 1, j] + 1;
                    int left = matrix[i, j - 1] + 1;
                    int diag = matrix[i - 1, j - 1] + cost;
                    matrix[i, j] = Math.Min(above, Math.Min(left, diag));
                }
            }
            return matrix[n, m];
        }/// <summary>
        /// 计算两个字符串的相似度
        /// </summary>
        /// <param name="source">来源字符串</param>
        /// <param name="target">目标字符串</param>
        /// <returns>相似度</returns>
        public static double CalcSimilarity(this string source, string target)
        {
            int n = source.Length;
            int m = target.Length;
            if (n == 0 || m == 0)
                return 0;
            int distance = source.CalcDistance(target);
            int max = Math.Max(n, m);
            return 1.0 * (max - distance) / max;
        }
    }