The dimensionality of cosine similarity refers to how you describe a given chunk of text, not how long or short the text itself is. It's easy for humans to visu

The dimensionality of cosine similarity refers to how you describe a given chunk of text, not how long or short the text itself is. It's easy for humans to visualize cosine similarity between two-dimensional vectors: draw two angles on graph paper, starting from the origin and going at some angle for some distance (normally 0-1) from the origin. You can visually understand that a 45-degree angle is far from a 270-degree angle, unless both happen to be very very short. But that is almost of negative help in describing what's going on here: the vectors in question have hundreds (or more!) dimensions, and are (except very abstractly) impossible for humans to visualize. Cosine similarity only becomes useful, and interestingly becomes counterintuitively useful, when used at these higher dimensions. My point was that the article doesn't describe the above.