I'm currently working on a project that relies on the clustering of documents into an unknown number of clusters, based on a similarity threshold (ideally using cosine distance between tf-idf vectors).
I'm attracted to elasticsearch for the project due to the 'out-of-the-box' similarity metrics provided when querying by string, however, I'm looking for some guidance as I'm very new to this. If anyone could provide any critique of the following approach, I'd be very grateful.
Is this whole approach horrible and inefficient? How feasible is this? Am I asking 'too much' of ES for this task?
Any help would be greatly appreciated, sorry for the long read. Thanks :)