Polarization is implicated in the erosion of democracy and progression to violence, which makes polarization properties large algorithmic content selection systems (recommender systems) a matter concern for peace security. While algorithm-driven social media do not seem be primary driver at country level, they could useful intervention point polarized societies. This paper examines depolarizati...

Recommender systems (RSs), as used by Netflix, YouTube, or Amazon, are one of the most compelling success stories AI. Enduring research activity in this area has led to a continuous improvement recommendation techniques over years, and today's RSs indeed often capable make astonishingly good suggestions. With countless papers being published on topic each year, might think problem is almost sol...

In this paper, we present new extensions to traditional approaches to recommender systems by making recommender systems support data warehousing capabilities. In particular, we propose recommender systems to work in multidimensional settings as opposed to the traditional twodimensional user/item environments. We also propose recommender systems to support rich profiling and OLAP capabilities.

We introduce HRS, a recommender that exploits user reviews and identifies the features that are most likely appealing to users. HRS incorporates this knowledge into the recommendation process to generate a list of top-k recommendations, each of which is paired with an explanation that (i) showcases why a particular item was recommended and (ii) helps users decide which items, among the ones rec...