I'm reading the book "Collective Intelligence" and in one chapter they introduce how to measure similarity between users on a movie review website with euclidean distance.
Now are the movies rated all on the scale from 1-5. But what if I want to find similar users based on features like - lets say body height, body width, weight and ratio of eye-distance to nose-length. This features operate on different scales, so e.g. body height would influence the distance much more than the eye-nose ratio.
My question is what is the best way to approach this example. Should one use a different distance measure (which?), or normalize the data somehow and use euclidean distance?