This has a lot of practical applications. For example Artsy (https://www.artsy.net) builds a K-nearest neighbor graph for its artworks. For example, scroll down to related results in Warhol's "Mushroom Soup" in https://www.artsy.net/artwork/andy-warhol-mushroom-soup to find Damien Hirst's "Chicken from Last Supper". The data is done by humans, but the related algorithm is based on K-nearest neighbors.

We started with this basically what's in the article, then used Locality Sensitive Hashing (http://www.mit.edu/~andoni/LSH) as a real-time approximation and today we use NNDescent from this priceton paper: http://www.cs.princeton.edu/cass/papers/www11.pdf

I'll look at these and then consider doing an information retrieval extension with KNN.

can you do one with DBSCAN

Absolutely can do. I'll put it in my queue of write ups to do. Thank you for the suggestion! Hope you enjoyed this write up.

I enjoyed, and looking forward to your posts in future. I just dropped a comment on your website.(@gansai9)