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This paper investigates the use of automatically extracted visual features of videos in the context of recommender systems and brings some novel contributions in the domain of video recommendations. We propose a new content-based recommender system that encompasses a technique to automatically analyze video contents and to extract a set of representative(More)
In this paper, we present an ongoing work that will ultimately result in a movie recommender system based on the Mise-en-Scène characteristics of the movies. We believe that the preferences of users on movies can be well described in terms of the mise-en-scène, i.e., the design aspects of movie making influencing aesthetic and style. Examples of(More)
NoSQL databases have emerged as a backend to support Big Data applications. NoSQL databases are characterized by horizontal scal-ability, schema-free data models, and easy cloud deployment. To avoid overprovisioning, it is essential to be able to identify the correct number of nodes required for a specific system before deployment. This paper benchmarks and(More)