[HN Gopher] Ask HN: Why do recommender systems not seem good?
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Ask HN: Why do recommender systems not seem good?
I personally find recommender systems on platforms that I am on to
be very poor. I would expect with all the effort that has gone
into these, and all the progress in machine learning, these systems
would be fantastic and provide recommendations that I really enjoy.
But they don't. YouTube seems to have a massive recency bias and
music, film, and TV recommendations rarely end up being things I
enjoy.
Author : subharmonicon
Score : 10 points
Date : 2024-02-26 22:23 UTC (37 minutes ago)
| andy99 wrote:
| They are not optimized for what you enjoy, or even want.
|
| A passable analogy: you buy a car and get hassled, often hard-
| sold for a pre-paid maintenance package, tire insurance,
| financing insurance, undercoating, bla bla. You don't want any of
| it but it's what they push the hardest.
| wenc wrote:
| They work well if there are lots of people like you (ie you are a
| normie).
|
| All machine learning algorithms struggle at the edges -- they're
| very good at predicting aggregate behavior.
|
| If you have eclectic tastes there's probably not enough data on
| your demographic.
| add-sub-mul-div wrote:
| I have a theory that some people's likes are based on things that
| are too subtle, intangible, or unrepeatable to identify, predict,
| or data mine. At least that's what I've figured is why
| recommendation systems don't work for me and why I run into so
| many dead ends when I try to use clear aspects of what I like to
| find other likes.
| smrtinsert wrote:
| Excellent question. All the streaming providers only seem to
| suggest movies from my generation and absolutely nothing new. It
| feels like they have created an ultra generic advertising profile
| for me and only use that to recommend content. It's incredibly
| depressing. Youtube is slightly better but still extremely
| siloed. No amount of "algorithm training" seems to help.
| behnamoh wrote:
| You buy a $1000 scooter from Amazon and then it keeps
| recommending you other good scooters for months, even after the
| return window for the first one is closed.
|
| Yeah, you'd expect more from ML at this point. I wonder how much
| of ML research actually gets utilized in industry.
| neovialogistics wrote:
| 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.
| JohnMakin wrote:
| Because the recommendations aren't for _you_ - they are what
| generates the most amount of ad revenue for them, which roughly
| correlates to the amount of money advertisers are willing to
| spend to reach people like you. That is in no way a guarantee
| that the recommendations will be good for you, because the
| incentives are not aligned.
| superasn wrote:
| I think a lot of recommendation system take only the positive
| signals into account but don't take the negative signals that
| seriously.
|
| So If I like and disliked 10 movies just don't show me movies
| from users who also liked these. First, filter or downgrade all
| users who liked what I disliked and then create my
| recommendations.
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