[LintCode] Cosine Similarity 余弦公式 - Grandyang - 博客园

[LintCode] Cosine Similarity 余弦公式 - Grandyang - 博客园
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]).

Have you met this question in a real interview? 

Yes

Example

Given A = [1, 2, 3], B = [2, 3 ,4].
Return 0.9926.
Given A = [0], B = [0].
Return 2.0000

    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);
    }

Read full article from [LintCode] Cosine Similarity 余弦公式 - Grandyang - 博客园