嘿,亲!知识可是无价之宝呢,但咱这精心整理的资料也耗费了不少心血呀。小小地破费一下,绝对物超所值哦!如有下载和支付问题,请联系我们QQ(微信同号):78630559
本次赞助数额为: 5 元微信扫码支付:5 元
请留下您的邮箱,我们将在2小时内将文件发到您的邮箱
文本相识度查询
public class LevenshteinDistance
{
#region 私有变量
/// <summary>
/// 字符串1
/// </summary>
private char[] _ArrChar1;
/// <summary>
/// 字符串2
/// </summary>
private char[] _ArrChar2;
/// <summary>
/// 统计结果
/// </summary>
private Result _Result;
/// <summary>
/// 开始时间
/// </summary>
private DateTime _BeginTime;
/// <summary>
/// 结束时间
/// </summary>
private DateTime _EndTime;
/// <summary>
/// 计算次数
/// </summary>
private int _ComputeTimes;
/// <summary>
/// 算法矩阵
/// </summary>
private int[,] _Matrix;
/// <summary>
/// 矩阵列数
/// </summary>
private int _Column;
/// <summary>
/// 矩阵行数
/// </summary>
private int _Row;
#endregion
#region 属性
public Result ComputeResult
{
get { return _Result; }
}
#endregion
#region 构造函数
public LevenshteinDistance(string str1, string str2)
{
this.LevenshteinDistanceInit(str1,str2);
}
public LevenshteinDistance()
{
}
#endregion
#region 算法实现
/// <summary>
/// 初始化算法基本信息
/// </summary>
/// <param name="str1">字符串1</param>
/// <param name="str2">字符串2</param>
private void LevenshteinDistanceInit(string str1,string str2)
{
_ArrChar1 = str1.ToCharArray();
_ArrChar2 = str2.ToCharArray();
_Result = new Result();
_ComputeTimes = 0;
_Row = _ArrChar1.Length 1;
_Column = _ArrChar2.Length 1;
_Matrix = new int[_Row, _Column];
}
/// <summary>
/// 计算相似度
/// </summary>
public void Compute()
{
//开始时间
_BeginTime = DateTime.Now;
//初始化矩阵的第一行和第一列
this.InitMatrix();
int intCost = 0;
for (int i = 1; i < _Row; i )
{
for (int j = 1; j < _Column; j )
{
if (_ArrChar1[i - 1] == _ArrChar2[j - 1])
{
intCost = 0;
}
else
{
intCost = 1;
}
//关键步骤,计算当前位置值为左边 1、上面 1、左上角 intCost中的最小值
//循环遍历到最后_Matrix[_Row - 1, _Column - 1]即为两个字符串的距离
_Matrix[i, j] = this.Minimum(_Matrix[i - 1, j] 1, _Matrix[i, j - 1] 1, _Matrix[i - 1, j - 1] intCost);
_ComputeTimes ;
}
}
//结束时间
_EndTime = DateTime.Now;
//相似率 移动次数小于最长的字符串长度的20%算同一题
int intLength = _Row > _Column ? _Row : _Column;
_Result.Rate = (1 - (double)_Matrix[_Row - 1, _Column - 1] / intLength).ToString().Substring(0, 6);
if (_Result.Rate.Length > 6)
{
_Result.Rate = _Result.Rate.Substring(0, 6);
}
_Result.UseTime = (_EndTime - _BeginTime).ToString();
_Result.ComputeTimes = _ComputeTimes.ToString() " 距离为:" _Matrix[_Row - 1, _Column - 1].ToString();
}
/// <summary>
/// 计算相似度
/// </summary>
/// <param name="str1">字符串1</param>
/// <param name="str2">字符串2</param>
public void Compute(string str1,string str2)
{
this.LevenshteinDistanceInit(str1, str2);
this.Compute();
}
/// <summary>
/// 初始化矩阵的第一行和第一列
/// </summary>
private void InitMatrix()
{
for (int i = 0; i < _Column; i )
{
_Matrix[0, i] = i;
}
for (int i = 0; i < _Row; i )
{
_Matrix[i, 0] = i;
}
}
/// <summary>
/// 取三个数中的最小值
/// </summary>
/// <param name="First"></param>
/// <param name="Second"></param>
/// <param name="Third"></param>
/// <returns></returns>
private int Minimum(int First, int Second, int Third)
{
int intMin = First;
if (Second < intMin)
{
intMin = Second;
}
if (Third < intMin)
{
intMin = Third;
}
return intMin;
}
#endregion
}
/// <summary>
/// 计算结果
/// </summary>
public struct Result
{
/// <summary>
/// 相似度
/// </summary>
public string Rate;
/// <summary>
/// 对比次数
/// </summary>
public string ComputeTimes;
/// <summary>
/// 使用时间
/// </summary>
public string UseTime;
}