This chapter studies state-of-the-art research related to multimedia recommender systems
(MMRS), focusing on methods that integrate multimedia content as side information to …

As of today, most movie recommendation services base their recommendations on
collaborative filtering (CF) and/or content-based filtering (CBF) models that use metadata …

We propose a multi-modal content-based movie recommender system that replaces human-
generated metadata with content descriptions automatically extracted from the visual and …

Abstract An intelligent Recommendation App has been developed to assist caregivers. This
project's primary objective is to assist parents in determining whether a particular …

Abstract Information Retrieval (IR) systems have a wide range of impacts on consumers. We
offer maps to help identify goals IR systems could—or should—strive for, and guide the …

Recommender systems are increasingly being used in university or online education.
However, recommender systems still have not found major usage in K12 education. This …

The goal of this work is to formally provide a general definition of a multimedia
recommendation system (MMRS), in particular a content-based MMRS (CB-MMRS), and to …

Recommender systems (RS) in their majority focus on an average target user: adults. We
argue that for non-traditional populations in specific contexts, the task is not as …

Today, preschool-aged children have an abundance of digital content to choose from, with
some more desirable than others from a developmental perspective. We aim to describe and …

Children are common users of recommender systems (RSs) when watching videos on
streaming services, accessing information on the web or playing games, being tablets or …