Calogero Zarba, Neodata Intelligence s.r.l., Italy

Recommendation algorithms for online news
Online newspapers are blooming because the online medium offers advantages that are simply not available in the printed medium.

In particular, online news can be personalized.

With personalization, a user visiting an online newspaper website can go to a personalized webpage. Different users will see different versions of the personalized webpage. The content of the personalized webpage is generated by using a recommender system, which uses a recommendation algorithm (or a combination thereof) in order to select articles specifically targeted to the interests of the user.

In this tutorial we review the most commonly used recommendation algorithms for online news. In particular, we review algorithms based on collaborative filtering, algorithms based on content-based filtering, as well as some hybrid approaches.