# Feature idea: 5 artists that span my taste

**URL:** https://community.metabrainz.org/t/feature-idea-5-artists-that-span-my-taste/531033
**Category:** ListenBrainz
**Created:** [April 28, 2021, 5:46pm UTC](https://community.metabrainz.org/t/feature-idea-5-artists-that-span-my-taste/531033 "2021-04-28T17:46:06Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![Jovial](https://community.metabrainz.org/letter_avatar_proxy/v4/letter/j/0ea827/32.png) [@Jovial](https://community.metabrainz.org/u/Jovial)
#### Post date: [April 28, 2021, 5:46pm UTC](https://community.metabrainz.org/t/feature-idea-5-artists-that-span-my-taste/531033/1 "2021-04-28T17:46:06Z")

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A friend asked me to give 5 bands that show what I’m into. Initially I was going to give him my top 5 by playcount. But that is potentially less interesting. Imagine a user who listens mostly to 10 artists, 6 of them rock groups. The top 5 could be polluted with rock groups, while hiding indie or jazz groups the user also likes.

If we can algorithmically define a band’s similarity to other bands, then choose a representative band from that group, we could compile 5 bands that cover as much of the projected space as possible. (That’s a somewhat large “if”.)

For example:  
Map every band a user listens to into N-dimensional space. (Say, 2-dimensional for easier visualization). Could use [multidimensional scaling (MDS)](https://nherger.github.io/posts/mds-hierclust) or any unsupervised method.  
Split the bands into K clusters, maximizing the distance between the clusters (typical of clustering algorithm). A representative median (i.e., an actual band and not a combination of several bands) should be chosen, so K-medians could be used for example. ([Further reading](https://en.wikipedia.org/wiki/K-means_clustering) and [page 2](https://en.wikipedia.org/wiki/K-medians_clustering)). If K=5, we choose 5 bands to represent a user’s taste.

I don’t know how this would handle a user who only has J\<K major interests/genres. If I listen to 90% jazz I might not want my “representative” clustering to pick 1 jazz artist and some other bands I barely heard (pop, country, rap, ambient).

If some 2-dimensional projection is used, this could potentially lead to an interactive graph. Each point would be a band, and the user could explore similar artists. Quick mockup:

 ![image](https://community.metabrainz.org/uploads/default/original/3X/9/6/961e26a5441c9e11b75a1b34c009644f3cb48bab.png)