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A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels by Felicioni, Nicolò; Dacrema, Maurizio Ferrari; Cremonesi, Paolo is a scholarly article available to read on EtoBox.

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Many video-on-demand and music streaming services provide the user with a page consisting of several recommendation lists, i.e. widgets or swipeable carousels, each built with a specific criterion (e.g. most recent, TV series, etc.). Finding efficient strategies to select which carousels to display is an active research topic of great industrial interest. In this setting, the overall quality of the recommendations of a new algorithm cannot be assessed by measuring solely its individual recommendation quality. Rather, it should be evaluated in a context where other recommendation lists are already available, to account for how they complement each other. This is not considered by traditional offline evaluation protocols. Hence, we propose an offline evaluation protocol for a carousel setting in which the recommendation quality of a model is measured by how much it improves upon that of an already available set of carousels. We report experiments on publicly available datasets on the movie domain and notice that under a carousel setting the ranking of the algorithms change. In particular, when a SLIM carousel is available, matrix factorization models tend to be preferred, while item-

Author

Felicioni, Nicolò; Dacrema, Maurizio Ferrari; Cremonesi, Paolo

Published

2021

Language

EN