Music recommender systems (MRSs) have experienced a boom in recent years, thanks to
the emergence and success of online streaming services, which nowadays make available …

Video summarization is the method of extracting key frames or clips from a video to generate
a synopsis of the content of the video. Generally, video is compressed before storing or …

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

Item features play an important role in movie recommender systems, where
recommendations can be generated by using explicit or implicit preferences of users on …

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

This tutorial introduces multimedia recommender systems (MMRS), in particular,
recommender systems that leverage multimedia content to recommend different media …

Video recordings are complex media types. When we watch a movie, we can effortlessly
register a lot of details conveyed to us (by the author) through different multimedia channels …

In the era of internet has embarked on World Wide Web for searching or knowing any
information about any topic which has resulted in humongous information load. Access to …

In this paper we introduce the MediaEval 2018 task Recommending Movies Using Content.
It focuses on predicting overall scores that users give to movies, ie, average rating …

In order to improve the accuracy of recommendations, many recommender systems
nowadays use side information beyond the user rating matrix, such as item content. These …