Do recommendation systems necessarily use machine learning algorithms? I am studying about evaluation of both recommendation systems and machine learning algorithms in recent times, trying to define a scope for my masters research. After some reading time I'm starting to understand several concepts, but one thing was not clear to me:

Do recommendation systems necessarily use machine learning algorithms?

I mean, I know these two can be used combined, but in most of the papers I read about recommender systems evaluation, they do not even mention anything about Machine Learning.

Also, if you can suggest some papers that I can read, I would be very grateful
There's nothing about a recommendation system that absolutely necessitates some kind of machine learning. Indeed, I've seen decision systems in use that were essentially just someone's idea about what the customer's preferences ought to be.

A recommender can be based on anything from a few ad-hoc 'common sense' rules, to a logistic regression someone did on some data a few years ago and whose parameters are hardcoded into the system, to a complicated ensemble of machine-learning algorithms that are regularly and constantly trained on new data.

The use of machine learning for recommender systems is partly driven by necessity, partly by fad (at least from what I have seen). If a simple recommender works well, and accurately predicts what the user wants, there's no need for a machine to learn anything. If there's a huge amount of data, hiding some very deep relationships that humans are unable to pick out, that's where machine learning becomes useful.