I have a web site that process text documents (typically 10-100 pages) submitted by users. Each time a user submits a document, I'd like to store a hash of the document, but I'd like similar documents to map to the same hash value. I essentially want to know whether a user is resubmitting a slightly changed document or a new document.
I don't store the documents, so I can only compare hash values and I can't compare the documents to each other.
I've done a lot of reading about MinHash and LSH, but these all seem to be based on having a corpus of a large number of documents and then finding similar documents within the corpus. I think these don't work for me because I need to compute my hash vector on a single document at a time without knowing anything about other documents.
In some ways I feel like this should be an easy problem. Something like computing a hash of a bag-of-words vector, but I'm struggling to figure out a good way to do this.
My comparison is based on text and not meaning so I don't need anything like word embeddings.