The best song randomizer I've seen described generates a permutation of songs, then "plots" them in n dimensional space with closeness being closeness being a weighted distance of closeness in the playlist and whatever metadata you have about them. (artist, genre, year, mood). Then you iteratively break the clumps until you can't find any or the number stops decreasing. If you still have clumps then you raise the bar for what is considered a clump and repeat until you hit zero.
However, I've used Spotify since 2014 and still experienced the same Shuffle behavior. Strange, perhaps I'm looking for it now, and introducing some sort of bias.
It is interesting, however, that a music playlist company took so long to realize people wouldn't like their original Shuffle implementation. I don't think any device or software I used before Spotify had such a remarkably bad Shuffle experience - including the original iPods and other, much older software and devices.
True. It's just that I don't think I've ever experienced Spotify's take on Shuffle anywhere else before, so it's shocking and frustrating, leading to a lot of "next, next, next" skipping.
https://en.wikipedia.org/wiki/Clustering_illusion
https://en.wikipedia.org/wiki/Poisson_clumping
The best song randomizer I've seen described generates a permutation of songs, then "plots" them in n dimensional space with closeness being closeness being a weighted distance of closeness in the playlist and whatever metadata you have about them. (artist, genre, year, mood). Then you iteratively break the clumps until you can't find any or the number stops decreasing. If you still have clumps then you raise the bar for what is considered a clump and repeat until you hit zero.