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@jainaayush05 I don't think the cosineDistance part will work. I'm pretty sure that the LSH hashing implementation would have to change in order for cosine distance to make sense. Do you have results to suggest otherwise? |
@jainaayush05 Any thoughts on the cosine distance not working with this implementation of LSH? |
The implementation of lsh is different for cosine and euclidean similarity.
If you are interested, this video series is a fantastic deep dive:
https://youtu.be/tlGocuyQ7F0
It's certainly possible to implement but it's not plug and play with the
current implementation. Also, the implementation for euclidean in this
plugin is actually more complicated than it needs to be.
I'm not maintaining any of this code anymore, so I'd rather not merge any
PRs. I don't really consider it a library so much as it's a proof of
concept. I think there are one or two forks floating around that other
people have extended and might be maintaining. Would love to maintain it
but there's only so much time in a day, and my current daily work is
unrelated.
…On Wed, Aug 28, 2019, 02:47 Sai ***@***.***> wrote:
@jainaayush05 <https://github.com/jainaayush05> Any thoughts on the
cosine distance not working with this implementation of LSH?
@alexklibisz <https://github.com/alexklibisz> If the filtering of
documents part of this pull request work, can that be added to your library?
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One of the biggest drawbacks of libs like annoy or Faiss is that it doesn't allow filtering of documents to be searched before finding nearest neighbours. This is something that can be solved using the changes I have suggested