Random thought. maybe bloom filters could be space efficient way to handle the filtering use case? I don't know much about them but AI says they are used to prove an ID is within a set
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I think for 1. and 2. RankProfiles is a solid approach
Let's go through the case with replies:
- user clicks on a note
- client loads all replies for that note
- extract the pubkeys of these replies
- client asks Vertex for the ranks of up-to 1000 pubkeys in a single call, with the user's preferred algorithm
- client hides replies from npubs with rank lower than the user's preferred threshold
- client ranks the other replies by their rank (or a custom formula like rank * zap amount).
Rank Profiles
This service sorts a provided list of pubkeys using the specified algorithm.
Example use cases:
Batched ranking of pubkeys
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It's an interesting idea but I don't see where exactly in the client you would need it.
- for the feed one uses follows
- for the replies, because on the relatively low number one can use the ranks directly (giving the user the ability to set a threshold).
Bloom filters are superior to RankProfiles when you are dealing with +10k pubkeys (not in the follow-list of the user) I think.
Am I missing something?