Description
Cosine similarity is a measure of similarity between two vectors of an inner product space that measures the cosine of the angle between them. The cosine of 0° is 1, and it is less than 1 for any other angle.
See wiki: Cosine Similarity
Here is the formula:
Given two vectors A and B with the same size, calculate the cosine similarity.
Return 2.0000 if cosine similarity is invalid (for example A = [0] and B = [0]).
Example
Given A = [1, 2, 3], B = [2, 3 ,4].
Return 0.9926.
Given A = [0], B = [0].
Return 2.0000
解题：按照公式计算，对特殊情况进行处理（数组不为空、分母不为0）。代码如下
public class Solution {
/*
* @param A: An integer array
* @param B: An integer array
* @return: Cosine similarity
*/
public double cosineSimilarity(int[] A, int[] B) {
// write your code here
if(A.length == 0 || B.length == 0)
return 2.0000;
int a = 0;
int b = 0;
int sum = 0;
for(int i = 0; i < A.length; i++){
a = a + A[i] * A[i];
b = b + B[i] * B[i];
sum = sum + A[i] * B[i];
}
if(a == 0 || b == 0)
return 2.000;
return (double)sum / (Math.sqrt(a) * Math.sqrt(b));
}
}