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Ask HN: Why do recommender systems not seem good?

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Re: Ask HN: Why do recommender systems not seem good?

#51

Post by bflesch »

asciimov wrote: post #36

You and your enjoyment is no longer center to the recommendations. Ads/money, engagement, and your time are the only metrics that matter. Results these days seem worse then the old days of Altavista and Lycos.

But this could also be self-reinforcing a local maximum while alienating more and more users. And then your data shows much better metrics for the cohort which puts up with the bad experience, because everyone else churns. This might work for some time, but I don't think it is sustainable.

Right now it feels everyone is ready to ditch Apple products, Twitter, Tesla, Amazon, YouTube, Gmail once something better comes around because of all these small quirks and weird UX things where you notice that the vendor's interests are just not aligned with you as a user/customer.

Re: Ask HN: Why do recommender systems not seem good?

#52

Post by yCombLinks »

bflesch wrote: post #50
ChadNauseam wrote: post #23

It's weird but tiktok is the only one that seems to do a good job. Seriously. The tiktok recommendation algorithm is so good. And then for ads, instagram seems to be the only one that does a good job. I regularly get ads for things I actually want from instagram, never from any other platform.

You might reconsider your thoughts when you recognize the fact that TikTok's first priority is not to make money but to deliver pro-russian and pro-chinese propaganda messages into your brain.

Not sure how that's related to the quality of recommendations the algorithm gives.

Re: Ask HN: Why do recommender systems not seem good?

#53

Post by Leftium »

ants_everywhere wrote: post #35
Leftium wrote: post #22

Earlier quoted context omitted.

“Why is Amazon trying to sell me an X? I just bought an X. Idiots!” Amazon is not an idiot: > You need two insights here: > 1) Conditional probability is a mathematical technology that does exist. > 2) Buying X is not entirely random across the population. > The ways X is not random vary based on the good [math]. Consider refrigerators. > You probably buy one every ten years. If I don't know where you are in your ref…

That's kind of a dismissive way to say "maybe it's optimized for buyer's remorse or returns?" Maybe it is, but I'm not totally convinced. For one it doesn't explain why Amazon would recommend literally the same SKU so often. Also, does Amazon really want to incentivize returning large items like fridges? And the poker thing from the original post > People who are compensated strictly based on their ability to predict…

patio11 has interesting insights, but does give off an "angry nerd" vibe

Whether poker players are predicting the future or not, I would argue Amazon is doing the same thing:

- Each potential customer can be considered a hand with a certain probability.

- Amazon is sizing their "bet" (ad budget) according to the probability that customer will convert.

I also agree with this observation about poker, and can imagine Amazon using a similar strategy: https://hw.leftium.com/#/item/39462238

Successful marketers were already teaching this decades ago: https://thegaryhalbertletter.com/newsletters/direct_marketin...

Re: Ask HN: Why do recommender systems not seem good?

#54

Post by bflesch »

yCombLinks wrote: post #52
bflesch wrote: post #50

Earlier quoted context omitted.

You might reconsider your thoughts when you recognize the fact that TikTok's first priority is not to make money but to deliver pro-russian and pro-chinese propaganda messages into your brain.

Not sure how that's related to the quality of recommendations the algorithm gives.

Because the algorithm has been shown to recommend nice videos which show that the russians have very good reasons to annex ukraine, or that the chinese economy is going so well, or that this right-wing fringe party has actually very good answer to the speech of a government official.

But yes, it's all just a coincidence and does not affect the quality of recommendations.

TikTok recommends 9 good videos and then 1 where they explain the political topic of the day from their perspective because you are located in Europe.

Re: Ask HN: Why do recommender systems not seem good?

#55

Post by myk9001 »

behnamoh wrote: post #11
neovialogistics wrote: post #8

Scale. Providing accurate recommendation algorithms for thousands+++ of people across thousands+++ of data items is surprisingly expensive in compute and electricity. For any one user, sure you can do whatever you like. When you divide your resources across your userbase the prices get larger and larger.

Sam Altman said something about Instagram which is interesting. He said at midnight, the quality of the recommendations is higher because few people are on the platform. Does it mean at peak hours IG switches to a simpler algorithm? Otherwise, why would the quality of a RS drop during those hours?

Did Mr Altman happen to elaborate on what time zone he had in mind? ;)

Re: Ask HN: Why do recommender systems not seem good?

#56

Post by scj »

Not an expert, but as a learning experience I wrote a board game recommender years ago based on data from boardgamegeek.

There were a lot of little things that added up:

  1. Everyone interprets the 1.0 - 10.0 rating scale differently.
  2. Most users just rate the same, universally known games.
  3. For the other users, the games they've played are usually really different.  It's a sparse matrix.
Every attempt at game-to-game analysis flopped. User-to-user analysis seemed to work better.

I managed to find a few dozen similar users. Found some hidden gems by going through their pages manually. Fewer than I would have hoped though.

Re: Ask HN: Why do recommender systems not seem good?

#57

Post by sobriquet9 »

Because to make good, personalized recommendations they need to know what you don't know, and there isn't a good source of information about it.

For example, if you have not seen The Shawshank Redemption, chances are you will like it. It's #1 among IMDB top 250 list. But a recommender does not know if you've seen it. If you've seen it already, it's a bad recommendation.

So the same recommendation for the same person can be good today and bad tomorrow, depending on something recommender engine does not see. That makes it very difficult to tune and measure performance.

Re: Ask HN: Why do recommender systems not seem good?

#58

Post by alamortsubite »

morkalork wrote: post #42
alamortsubite wrote: post #31

Earlier quoted context omitted.

It's a tricky balance. The weaker the quality of recommendations, the more likely a user is to switch to another platform.

This falls apart when you look at platforms like Netflix. They recommend their original content because they don't pay royalties. The platforms aren't interchangeable though. If you want Disney movies, you aren't getting them anywhere else but Disney plus.

Sure, but what I mean to say is that, at a certain point, it's very easy to watch a Disney movie instead of a Netflix movie (or neither).

Re: Ask HN: Why do recommender systems not seem good?

#60

Post by jgwil2 »

MivLives wrote: post #21

I think that the issue is that it's always assumed that similar things are a better recommendation. The issue is at least for myself and other people I've talked to about that a lot of times we're looking for something different from the last thing. For example if I spend a week listening to vintage surf rock the recommendations that could be given might be 60s pop, or more surf rock. But what actually I wanted was t…

I think Pandora is one of the better systems out there for this. You prime it with a few examples of stuff you like but then it seems to continually drop slightly different stuff on you to see how you react.
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