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Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

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Re: Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

#31

Post by costco »

varenc wrote: post #24

I love this site, and the approach! Great seeing someone making good use of Goodreads data. Sadly my experience with the book recommender isn't too great because of the 64 book limit. If I import either the most recent or least recent 64 book, 95% of the books it recommends to me are books I've read. Though it was helpful for spotting a few books I've read that I didn't log on Goodreads. Guess I'm pretty consistent.

I think I will expand the input books limit (sadly requires retraining) and or the output books limit of 30.

Re: Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

#33

Post by mcbrit »

mcbrit wrote: post #29

I don't know. I entered, trying to be popular but at least slightly? opiniated: Tigana, Hyperion, A Fire Upon the Deep, Blindsight, Moby Dick and I got a list. Sure, read all that or wasn't interested for reasons, I added (only Neuromancer on initial recommendations): Neuromancer, VALIS, Quantum Thief, Towing Jehovah. List did not get more interesting. Book recommendations are still kind of difficult.

If I provide that list, a (real) person doesn't ask me if I've read the Hobbit.

Re: Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

#36

Post by costco »

__alexander wrote: post #34

Care to share the scrapped data? I would love to play around with it.

Not sure if I can. At the very least book descriptions most likely could not be distributed. There is an academic dataset with around 200M reviews though: https://cseweb.ucsd.edu/~jmcauley/datasets/goodreads.html

Re: Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

#37

Post by teaearlgraycold »

mcbrit wrote: post #29

I don't know. I entered, trying to be popular but at least slightly? opiniated: Tigana, Hyperion, A Fire Upon the Deep, Blindsight, Moby Dick and I got a list. Sure, read all that or wasn't interested for reasons, I added (only Neuromancer on initial recommendations): Neuromancer, VALIS, Quantum Thief, Towing Jehovah. List did not get more interesting. Book recommendations are still kind of difficult.

I don’t think past liked books are nearly enough information to provide a good book for you today. You need a lot more information about the state of someone’s mind.

Re: Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

#38

Post by MattGrommes »

This is cool but I'd love the option to filter out the author of the book you entered. I put in Shroud by Adrian Tchaikovsky and almost all the books are others by him, which is fine but doesn't really mix up the stuff I'm reading.

Re: Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

#39

Post by bigskydog »

costco wrote: post #28
skayvr wrote: post #22

I've worked in recommender systems for a while, and it's great to see them publicized. SASRec was released in 2018 just after transformer paper, and uses the same attention mechanism but different losses than LLMs. Any plans to upgrade to other item/user prediction models?

I'm not an expert by any means but as far as sequential recommendations go, aren't SASRec and its derivatives pretty much the name of the game? I probably should have looked into HSTUs more. Also this / sparse transformers in general: https://arxiv.org/pdf/2212.04120

Recommend OneRec which is an improvement of HSTU and it recently became open source

Re: Show HN: I scraped 3B Goodreads reviews to train a better recommendation model

#40

Post by mcbrit »

teaearlgraycold wrote: post #37
mcbrit wrote: post #29

I don't know. I entered, trying to be popular but at least slightly? opiniated: Tigana, Hyperion, A Fire Upon the Deep, Blindsight, Moby Dick and I got a list. Sure, read all that or wasn't interested for reasons, I added (only Neuromancer on initial recommendations): Neuromancer, VALIS, Quantum Thief, Towing Jehovah. List did not get more interesting. Book recommendations are still kind of difficult.

I don’t think past liked books are nearly enough information to provide a good book for you today. You need a lot more information about the state of someone’s mind.

You're talking to a dude. (in my case.) I mentioned 8 books.

I won't tell you exactly what to do, but one way to do it is to measure your surprise with me choosing each of those 8 books when you provide a recommendation back to me of what I should read next. I think I get kind of that experience talking to someone about books.

The algorithm didn't do that.

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