Dimensionality reduction for NLP applications being forgotten..? [D]

Ok so when I was doing my thesis a few years back, I wrote a whole section on why dimensionality reduction (DR) was important, and I remember arguing for it by illustrating something along the lines of the concept of distance losing significance in high dimensionality. I also remember that some of the methods I used for clustering worked better in lower dimensions, and so, DR was not just for visualization purposes (which I feel is what I see it …

applications concept dimensionality machinelearning nlp significance something thesis