Chapter 14. Future of recommender systems

 

In this final chapter, you’ll go back to the future:

  • You’ll look at a short summary of the book.
  • I’ll provide a list of topics to learn next if you want to continue your voyage into the exciting world of recommender systems.
  • Although nobody knows what the future of recommender systems holds, I’ll give you my best bet and then some final thoughts.

It has taken me three years to arrive at writing this sentence; I hope your travel time has been a bit faster. I wish I could say that now you know everything about recommender systems and that you can venture forth as an expert who understands all recommender algorithms. And, more importantly, that you’ll never be surprised by anything on this topic again. You’ve come a long way, but from here to becoming an expert is still a long journey.

In this book, you learned the basics, enough to get you started and equip you for digging deeper into the subject. But don’t only read. Play around with new algorithms or get more intimately familiar with the ones described in the book. You’ll find many improvements and tricks to make each of them work better.

Hopefully, the MovieGEEKs site provided the basics for how to load different kinds of data and try out some of the things you learned from reading this book. Remember that MovieGEEKs was implemented to make recommender systems and algorithms easy to understand and has many places where it can be optimized.

14.1. This book in a few sentences

14.2. Topics to study next

14.2.1. Further reading

14.2.2. Algorithms

14.2.3. Context

14.2.4. Human-computer interactions

14.2.5. Choosing a good architecture

14.3. What’s the future of recommender systems?

User profiles

context

Algorithms

Privacy

Architecture

Surprising recommendations

14.4. Final thoughts