I'm working on an experiment which is essentially a content recommendation service.
I have a set of content items in the form of articles, tweets, blog posts etc which have had a set of tags associated with them based on their contents.
I also have a set of user profiles with information on the users personality, interests, dislikes, activities etc.
Each user profile then has a column for liked and disliked tags to show which content items they would enjoy reading.
I would like to be able build a service that when passed a new user profile, returns a set of tags (generated from similar existing user profiles) that can be used to find content items that the new user would enjoy reading.
This is my first experiment with machine learning so I was wondering if someone could give me some advice on how to achieve this, or an approach to get started.
Many thanks in advanced! Harry