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]).
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Example
Given A = [1, 2, 3], B = [2, 3 ,4].
Return 0.9926.
Given A = [0], B = [0].
Return 2.0000
这道题让我们求两个向量之间的余弦值，而且给了我们余弦公式，唯一要注意的就是当余弦值不存在时，返回2.0，其余的照公式写即可，参见代码如下：
class Solution { public: /** * @param A: An integer array. * @param B: An integer array. * @return: Cosine similarity. */ double cosineSimilarity(vector<int> A, vector<int> B) { // write your code here double nA = norm(A), nB = norm(B), m = 0; if (nA == 0 || nB == 0) return 2.0; for (int i = 0; i < A.size(); ++i) { m += A[i] * B[i]; } return m / (nA * nB); } double norm(vector<int> V) { int res = 0; for (int i = 0; i < V.size(); ++i) { res += V[i] * V[i]; } return sqrt(res); } };
本文转自博客园Grandyang的博客，原文链接：余弦公式[LintCode] Cosine Similarity，如需转载请自行联系原博主。
