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.

In this era when every aspect of society is accelerating, people are always seeking improvement to stay competitive in their careers. E-learning systems fit into the ever challenging situation and provide learners with remote learning opportunities abundant resources. Facing numerous resources online, users need support deciding which course take, thus recommender applied personalized services ...

Systems able to suggest items that a user may be interested in are usually named as Recommender Systems. The new emergent field of Recommender Systems has undoubtedly gained much interest in the research community. Although Recommender Systems work well in suggesting books, movies and items of general interest, many users express today a feeling that the existing systems don’t actually identify...

Recommender Systems apply machine learning and data mining techniques to filter undetected information and can predict whether a user of a system would like a given resource based on his/her interests and preferences. To date a number of recommendation algorithms have been proposed, where Collaborative Filtering (CF) and Content-Based Filtering (CBF) are the two most famous and adopted recommen...