Hi, I see, hopefully you will be willing to participate in further testing (for example, in beta) when the project is in better shape.

The only reason I bring the current alpha to the public is to test the concept and see if people are interested in it at all. I spent around 1 year (1 year of time, not of working hours) to make the current alpha, and there is no sense in spending one more year on a project nobody actually wants. For now, feedback was somewhat positive, so I want to continue and see what I will build next.

The main idea of my recommendation algorithm is to calculate the unique test for every user. It doesn’t and wouldn’t compare the tastes of different users to calculate assumptions. I hate this, and those kinds of recommendation algorithms seem to never work for me. When doing my research on the beginning of the project, I found that such algorithms were first used for social media, but I don’t feel these algorithms are correct (as I feel it, I can’t prove this with real numbers for now).

So, hopefully, Gamescovery recommendation algorithms wouldn’t have biases like "well everyone likes X so X”, since it never tries to compare 2 or more users. Besides that, Gamescovery will allow users to tweak the algorithm so that users can actually customize it to make the algorithm better for them. That doesn’t mean users will be able to completely change the behavior of the algorithm, but rather direct it in a direction they want.