I am new to machine learning so please bare with me. I'll try to keep this short and sweet.
We are building a makeup simulation and recommendation system. My part is to recommend a makeup which is personalized to the user and also on par with the current makeup trends. I will be building a set of rules with the help of a beautician that will say which makeup is suitable for a particular set of features.
The outputs will be makeup for: foundation, lipstick, eye shadow
The input features are (tentative): skin tone, hair colour, dress colour, morning/evening, type of event attending, etc
So after I build this set of rules, I will be able to select the appropriate makeup to the given input. What I need is to be able to recommend makeup that is also trending amongst similar users because makeup styles are constantly evolving and I don't want to recommend the same makeup every time the same input features are given.
Also I want to be able to personalize the recommendation, i.e. if the user's history shows preference towards a nude makeup, I want the recommendation to be as close as possible to their preferences.
I'd appreciate any help regarding how I should proceed or what algorithms I should use or anything at all...!!