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Re:Netflix's Metaflow: Reproducible machine learning pipelines by ed25519FUUU on Monday December 21, 2020 @12:49PM (#25497312)
Do you have a counter example of a streaming service that does recommendations better?
Re:Netflix's Metaflow: Reproducible machine learning pipelines by DoofusOfDeath on Monday December 21, 2020 @01:12PM (#25497610)
Back when I used Netflix primarily for DVDs, the recommender system worked pretty well for me.

Much later, when they switched to simple thumbs up/down, the recommender system was entirely useless to me. (Not merely because of the dumbed-down rating system; the recommendations were genuinely bad.)

For the time in between, I'm not sure if the degradation was gradual, sporadic, or not degraded at all.

Re:Netflix's Metaflow: Reproducible machine learning pipelines by treis on Monday December 21, 2020 @01:32PM (#25497822)
It's pretty clear that their recommendation system and broader UX is designed, at least in part, to obfuscate how much content they have and how good it is. Back when it was DVDs and they had basically everything it was more about finding the next best thing for you. Now it's finding the next best thing they have and, preferably, something they own the rights to.
Re:Netflix's Metaflow: Reproducible machine learning pipelines by ramraj07 on Monday December 21, 2020 @04:02PM (#25499483)
If you add dvd subscriptions you can still get the original Netflix recommendations back, including sorting by top predicted rating (which to me is eerily amazing). I used to keep the dvd subscription mainly for the recommender, with the delivered blurays considered an extra bonus for very rare movies you couldn't stream even if you wanted to pay.
Re:Netflix's Metaflow: Reproducible machine learning pipelines by jointpdf on Monday December 21, 2020 @02:09PM (#25498242)
It’s not a home run for me, but I think Spotify recommendations are quite good. They clearly use some form of content based recommendation (extracting features from the music itself) blended with other methods. It seems to make an honest attempt at serendipity (songs/artists you may like but would otherwise be unlikely to discover).

I still think recommender engines should always enable some form of user tuning. If it doesn’t, then the recommender is a tool for services to control your behavior rather than the other way around.

Re:Netflix's Metaflow: Reproducible machine learning pipelines by octostone on Monday December 21, 2020 @03:06PM (#25498929)
Unless I’m missing this functionality somewhere (entirely possible), this lack of user-tuning has ruined Spotify recs for me, since I listen to entirely different playlists when working or meditating. I don’t check out recommendations to get the latest binaural beats or nature sounds, you know?

Although even before I started listening to Spotify while working etc, it seemed to have run out of things to recommend. My weekly discover playlist would be half things I’d already liked. So...who knows. But I miss the discovery functionality quite a bit.

Re:Netflix's Metaflow: Reproducible machine learning pipelines by jointpdf on Monday December 21, 2020 @04:16PM (#25499666)
I personally have a similar problem with the Spotify generated playlists, but I have persnickety preferences in electronic music so it often whiffs. But on the spectrum of recommendation engines it is on the side of honest effort (whereas Netflix is not). And for most users and musical palates I think it works great. Just yesterday my mom complimented me on my Christmas music DJ skills, but it was just the generated continuation of her own playlist.

Nothing really beats the recommendations of a human curator with exquisite taste, and just listening to new music nonstop and plucking out the gems as you go.

Re:Netflix's Metaflow: Reproducible machine learning pipelines by nwsm on Monday December 21, 2020 @03:14PM (#25499036)
I like Spotify's recommendations and have found lots of great artists from it. But now I feel I'm in a kind of Spotify-created rut of listening to static groups of artists. I have mostly stopped listening to my daily mixes because of this.

It's also easy to theorize about "big media" controlling what I listen to, so I still feel the need to do my own exploring, even when I'm getting recommended good fresh stuff.

Re:Netflix's Metaflow: Reproducible machine learning pipelines by toxik on Monday December 21, 2020 @04:33PM (#25499852)
The basic problem is understanding WHY I liked something. If I watch Tintin because it’s a cozy throwback to my childhood, that does not mean I would like every single Studio Ghibli movie in my recommendations.

Similarly, if I play Blacklist in the background as basically noise, I don’t want to see a bunch of related shows. I guess I could give it a thumbs down but I only do that for actually terrible movies.

Also Spotify and Apple music seem to have okay recommendations

Re:Netflix's Metaflow: Reproducible machine learning pipelines by kyawzazaw on Monday December 21, 2020 @04:45PM (#25499990)
Music is different from movies and television though. There are beats and rhythms that are easy to identify, lyrics easy to analyze and artists that are roughly categorized.
Re:Netflix's Metaflow: Reproducible machine learning pipelines by toxik on Monday December 21, 2020 @05:40PM (#25500543)
I feel like that’s not true, music is hard to analyze. Movies have synopses, and are generally categorized by their cast alone. I could figure out LotR belongs together from these datapoints, easily. Not to mention the fact that people watch trilogies in sequence like 99% of the time.
Re:Netflix's Metaflow: Reproducible machine learning pipelines by xiphias2 on Monday December 21, 2020 @01:02PM (#25497493)
Recommendations maybe not, but I love that in HBO I can sort by IMDB score to find great movies/series that I haven't watched yet. I just watched Broadwalk Empire as an example, and loved it.

Netflix doesn't show IMDB scores, so I have to check it always independently...it sucks.

Re:Netflix's Metaflow: Reproducible machine learning pipelines by qw3rty01 on Monday December 21, 2020 @01:19PM (#25497679)
Not a streaming service, but a lot of movie and TV databases tend to have decent recommendations for movies and shows similar to the one you're viewing. Although in this case, one could argue that the processing is offloaded to users who provide the recommendations.
Re:Netflix's Metaflow: Reproducible machine learning pipelines by taeric on Monday December 21, 2020 @12:59PM (#25497454)
I read this as a condemnation of recommender systems in general.

That or a ceding of recommendations to marketing. That feels too cynical, but more accurate.

Re:Netflix's Metaflow: Reproducible machine learning pipelines by JohnJamesRambo on Monday December 21, 2020 @08:52PM (#25502005)
Spotify's Discover Weekly has a pipeline straight into my brain and not only what I like, but what I will like in the future.
Re:Netflix's Metaflow: Reproducible machine learning pipelines by Reubend on Monday December 21, 2020 @01:59PM (#25498138)
The MovieLens recommender system works pretty well.
Re:Netflix's Metaflow: Reproducible machine learning pipelines by hogFeast on Monday December 21, 2020 @02:40PM (#25498570)
Spotify. Discover Weekly is very good, particularly considering they have only one chance to recommend with 30-40 songs, and quite a large universe to match on.

Not a streaming service but Google's Discover news is also very good (probably the best recommendations I have come across).