Autonomous driving is a highly relevant topic today, particularly among major car manufacturers attempting to lead in technological innovation and enhance driving safety. An autonomous vehicle must possess the capability to sense its environment and navigate without human intervention. Thus, it...
04b Atto di convegno in volume
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The evolution of online platforms over the past decades has radically transformed the way people discover music, and thanks to social media and music streaming services nowadays listeners have access to an ever-increasing amount of tracks and artists. Within these platforms, one of the goals of...
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Music recommendation has been relevant to the Recommender Systems (RecSys) community since the early days. With the growth of music streaming platforms, algorithmic recommendations have become critical in the music industry. However, many challenges are still wide open in the area of music...
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Ranking, recommendation, and retrieval systems are widely used in online platforms and other societal systems, including e-commerce, media-streaming, admissions, gig platforms, and hiring. In the recent past, a large "fair ranking"research literature has been developed around making these systems...
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Music listening in today's digital spaces is highly characterized by the availability of huge music catalogues, accessible by people all over the world. In this scenario, recommender systems are designed to guide listeners in finding tracks and artists that best fit their requests, having therefore...
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ACII is the premier international forum for presenting the latest research on affective computing. In this work, we monitor, quantify and reflect on the diversity in ACII conference across time by computing a set of indexes. We measure diversity in terms of gender, geographic location and academia...
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The understanding of the emotions in music has motivated research across diverse areas of knowledge for decades. In the field of computer science, there is a particular interest in developing algorithms to “predict” the emotions in music perceived by or induced to a listener. However, the gathering...
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Music Recommender Systems (mRS) are designed to give person-alised and meaningful recommendations of items (i.e. songs, playlists or artists) to a user base, thereby reflecting and further complementing individual users' specific music preferences. Whilst accuracy metrics have been widely applied...
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Listening to music radios is an activity that since the 20th century is part of the cultural habits for people all over the world. While in the case of analog radios DJs are in charge of selecting the music to be broadcasted, nowadays recommender systems analyzing users’ behaviours can...
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Grouping songs together, according to music preferences, mood or other characteristics, is an activity which reflects personal listening behaviours and tastes. In the last two decades, due to the increasing size of music catalogue accessible and to improvements of recommendation algorithms, people...