On vector similarity, I'd recommend a custom variant of the uncentered Pearson correlation as it better accounts for a balance between discreet and continuous values with vectors that might vary in length.

If you want to get real fancy you can use variants in combination with the uncentered Pearson correlation including variants of KL distance to RV distance calculations if you can fit your such that those become effective.