Trying to find papers about Similarity Metrics (Cosine, Euclidean, Pearson, Covariance, Manhattan)

I'm doing research involving recommendation systems using collaborative filtering and I'm trying to find papers that talk about the performance of these similarity metrics: Cosine, Euclidean, Pearson, Covariance, and Manhattan. I was also trying to find papers that talk about blending the metrics together to improve performance.