I understand what cosine similarity is and how to calculate it, specifically in the context of text mining (i.e. comparing tf-idf document vectors to find similar documents). What I'm looking for is some better intuition for interpreting the results/similarity scores I come up with.
My question: If I have a cosine similarity of less than 0.707 (i.e. an angle greater than 45 degrees), is is fair to say that those respective documents/vectors are more "different" (less "similar") since the angle between them is more orthogonal? My initial thought was 'yes,' but in practice for me so far it doesn't seem like that's the right way to read into the numbers.