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> Likes/dislikes are stored in local storage and compared against all stories using cosine similarity to find the most relevant stories. You're referring to us
by jzombie 2y ago
> Likes/dislikes are stored in local storage and compared against all stories using cosine similarity to find the most relevant stories.
You're referring to using the embeddings for cosine similarity?
I am doing something similar with stocks. Taking several decades worth of 10-Q statements for a majority of stocks and weighted ETF holdings and using an autoencoder to generate embeddings that I run cosine and euclidean algorithms on via Rust WASM.
- tiborsaas 2y ago> I am doing something similar with stocks. How well does it work?
- jzombie 2y agoIt seems to do well for a lot of searches, though some are questionable, but I believe that I know why. I'm training some different autoencoders to give it some different perspectives. The code lives here: https://github.com/jzombie/etf-matcher https://github.com/jzombie/etf-matcher The ad-hoc vector DB I've created lives here: https://github.com/jzombie/etf-matcher/blob/main/rust/src/data_models/ticker_vector_analysis.rs https://github.com/jzombie/etf-matcher/blob/main/rust/src/da...
- mahin 2y agoYes. Your project sounds cool, post it!
- jzombie 2y agoI just responded to an adjacent query with the info. https://news.ycombinator.com/threads?id=jzombie#42072665 https://news.ycombinator.com/threads?id=jzombie#42072665