Most common questions about recommender systems… →
How much data do I need? Given your data, you can use cross-validation or A/B testing to measure objectively the effectiveness of a recommender system.
We have this system in place, how do we know whether it is sane? See previous question.
My online recommender system is slow! Laziness is your friend: don’t recompute the recommendations each time you have new data.
My customers don’t like the recommendations!
- Keep expectations in check: recommending products is difficult and even human beings have trouble doing it,
- Explain the recommendations: nobody trusts a black box,
- Allow your users to freely explore your data and products in convenient and exciting ways.
Which algorithm is best? You should start with simple algorithms: it worked well enough for Amazon. To do better, a mix of different algorithms is probably best. You can combine them using ensemble methods.
