Skills based recommendation system

Question

Assuming that I have a list of Users with a list of skills: (each value is a different skill)

And a list of Tasks with a list of demanded skills:

Based on a manual classification that returned: (History list)

1. Task1 --> Recommended: User3
2. Task2 --> Reccomended: User5
3. Task3 --> Recommended: User6
4. Task4 --> Recommended: User9
5. Task5 --> Recommended: User8

Given a new Task(6) with skills (A,B,C...):

• What would be the best way or approach to build a recommendation system that learns with past data (history list) and returns a list of the "best ranked" users to perform this Task?

Answer 1

Why do you want to build a learning model?

Your problem seems to be a common assignment problem, all informations are known, absolute and deterministic. You don't need a ML algorithm for this.

Just vectorize your data as one-hot-vectors, define a distance function (you can look to the Hamming's distance).

Compute the distance vector beetween user/task and pick the one who minimize this distance.