The ACM Recommender Systems conference (RecSys) is the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. As RecSys brings together the main international research groups working on recommender systems, along with many of the world’s leading e-commerce companies, it has become the most important annual conference for the presentation and discussion of recommender systems research.
The 13th edition of RecSys took place in Copenhagen, Denmark during 16th-20th September 2019, where Lorenzo Porcaro (UPF) presented his work on the analysis of features' variation in analog and streaming radios, done in collaboration with Emilia Gómez (UPF / JRC)
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 automatically generate radios tailored to users' musical taste. Nonetheless, in both cases listening sessions do not depend on the listener choices, but on a set of external recommendations received. In this study, it is presented a model for estimating features' variation during listening sessions, comparing different scenarios, namely analog radios, personalized and not-personalized streaming radios.
Lorenzo Porcaro, Emilia Gómez. (2019) A Model for Evaluating Popularity and Semantic Information Variations in Radio Listening Sessions. 1st Workshop on the Impact of Recommender Systems (ImpactRS), at the 13th ACM Conference on Recommender Systems (RecSys 2019). Copenhagen, 16th-20th September.