graphefruit
commented
9 months ago Hello @Moritz-Langer,
thanks for getting here. This requests reminds a bit of this PR: https://github.com/graphefruit/Beanconqueror/pull/158
A recommandation system has been asked some times back in the last years. But in the end without having a real backend, a user login and a normalisation of data this might get tricky. The data are stored totally local, without any central point, and therefore a grinder A und User 1, and a grinder B und User 2, can be the same, but don't need to be.
Anyhow: If t here is something going, a opt-in needs to be given in the end.
Hello,
I want to propose a feature and if a decision is made to proceed in that direction, I might be able to implement the model behind the new feature.
The feature might be a big bonus for coffee consumers. It is a recommendation system based on community data and the preferences of the user. You can think of it as Amazons feature "People who liked this also liked..." (or similar name) or Spotify's Song Radio feature.
The main problem I see is the accumulation of data, maybe an opt-in system or a prompt in the app, whether people want to anonymously want to share their rating data would lead to enough input.
I have not yet looked into the code, but I think I´ve seen in a review, that the app stores this data on device and doesn't share with any central point, right?
I am up for a discussion about the topic.