对比两个文件相似度 余弦算法

文件A1 包含字符Bi 的个数BiN1,文件A2 包含的字符Bi 的个数BiN2

利用余弦算法:   相似度 = (B1N1*B1N2 +B2N1*B2N2+....+BiN1*BiN2)/(Math.sqrt(B1N1^2 +B2N1^2+....+BiN1^2)*Math.sqrt(B1N2^2 +B2N2^2+....+BiN2^2).

Math.sqrt() 代表开方。

具体代码如下：

public class SimilarDegreeByCos
{
    /*
     * 计算两个字符串(英文字符)的相似度，简单的余弦计算，未添权重
     */
     public static double getSimilarDegree(String str1, String str2)
     {
        //创建向量空间模型，使用map实现，主键为词项，值为长度为2的数组，存放着对应词项在字符串中的出现次数
         Map<String, int[]> vectorSpace = new HashMap<String, int[]>();
         int[] itemCountArray = null;//为了避免频繁产生局部变量，所以将itemCountArray声明在此

         //以空格为分隔符，分解字符串
         String strArray[] = str1.split(" ");
         for(int i=0; i<strArray.length; ++i)
         {
             if(vectorSpace.containsKey(strArray[i]))
                 ++(vectorSpace.get(strArray[i])[0]);
             else
             {
                 itemCountArray = new int[2];
                 itemCountArray[0] = 1;
                 itemCountArray[1] = 0;
                 vectorSpace.put(strArray[i], itemCountArray);
             }
         }

         strArray = str2.split(" ");
         for(int i=0; i<strArray.length; ++i)
         {
             if(vectorSpace.containsKey(strArray[i]))
                 ++(vectorSpace.get(strArray[i])[1]);
             else
             {
                 itemCountArray = new int[2];
                 itemCountArray[0] = 0;
                 itemCountArray[1] = 1;
                 vectorSpace.put(strArray[i], itemCountArray);
             }
         }

         //计算相似度
         double vector1Modulo = 0.00;//向量1的模
         double vector2Modulo = 0.00;//向量2的模
         double vectorProduct = 0.00; //向量积
         Iterator iter = vectorSpace.entrySet().iterator();

         while(iter.hasNext())
         {
             Map.Entry entry = (Map.Entry)iter.next();
             itemCountArray = (int[])entry.getValue();

             vector1Modulo += itemCountArray[0]*itemCountArray[0];
             vector2Modulo += itemCountArray[1]*itemCountArray[1];

             vectorProduct += itemCountArray[0]*itemCountArray[1];
         }

         vector1Modulo = Math.sqrt(vector1Modulo);
         vector2Modulo = Math.sqrt(vector2Modulo);

         //返回相似度
        return (vectorProduct/(vector1Modulo*vector2Modulo));
     }

     /*
      *
      */
     public static void main(String args[])
     {
         String str0 = "gold silver truck";
         String str1 = "gold silver truck";
         String str2 = "Shipment of gold damaged in a fire";
         String str3 = "Delivery of silver arrived in a silver truck";
         String str4 = "Shipment of gold arrived in a truck";
         String str5 = "gold gold gold gold gold gold";

         System.out.println(SimilarDegreeByCos.getSimilarDegree(str2, str4));
//         System.out.println(SimilarDegreeByCos.getSimilarDegree(str1, str3));
//         System.out.println(SimilarDegreeByCos.getSimilarDegree(str1, str4));
//         System.out.println(SimilarDegreeByCos.getSimilarDegree(str1, str5));
     }
}