[arcbyte]

Very cool product!

This really drives home for me the need to have some kind of separation in algorithms.

I have a few musical moods. I like country music and I like electronic music but I don't like to mix them. Moreover, I listen to a lot of Latin music sometimes but u really don't want to mix that with the other types. It's not necessarily a genre specific separarion even though I've presented it here that way.

All this to say, the first song that popped up for me to rate was latin. I'm not in that mood and don't want to rate latin or country songs right now. I don't want algorithms recommending things in those buckets to me right now. I don't want to swipe it away either tho because i might really like it when I'm in the latin mood. So my only option is to quit.

The product that solves this will be very useful

[samyndriss]

Many thanks! And really appreciate your feedback. This is indeed a challenging proposition but I really like the idea.

If I've understood correctly:

1. Assuming, your filter is set to ["country", "latin"], you would like the application to "take the hint" (for lack of a better expression) as you are disliking a certain genre (let's say country) and provide results that do not include the genre you're not in the mood for.

2. Further, you would like to have the results mixed i.e. currently, it provides you 50 tracks of a specific genre at a time.

3. Finally, you would like an option for "keeping a track on ice", that is, I don't want to listen to this right now but might later so don't completely eliminate it from the poll of options.

[secludedrelish]

> It's not necessarily a genre specific separarion even though I've presented it here that way.

> 1. Assuming, your filter is set to

My interpretation of OP is the following:

I have different situations for music. I might listen to certain tracks in the early morning, others when coding, and yet others at the gym. If I have song x, I can: like X in the morning, like X for coding, dislike for both, like it for both. Of course, expand the two options to n.

Just like Netflix has different recommendation profiles for different users in a family, music recommendation algorithms should have the ability to make distinct profiles for different moods of one user.