Live Session
Thursday Posters
Main Track
Towards Sustainability-aware Recommender Systems: Analyzing the Trade-off Between Algorithms Performance and Carbon Footprint
Giuseppe Spillo (University of Bari), Allegra De Filippo (University of Bologna), Cataldo Musto (Dipartimento di Informatica – University of Bari), Michela Milano (University of Bologna) and Giovanni Semeraro (University of Bari).
Abstract
In this paper, we present a comparative analysis of the trade-off between the performance of state-of-the-art recommendation algorithms and their sustainability. In particular, we compared 18 popular recommendation algorithms in terms of both standard metrics (i.e., accuracy and diversity of the recommendations) as well as in terms of energy consumption and carbon footprint on three different datasets. In order to obtain a fair comparison, all the algorithms were run based on the implementations available in a popular recommendation library, i.e., RecBole, and used the same experimental settings. The outcomes of the experiments clearly showed that the choice of the optimal recommendation algorithm requires a thorough analysis, since more sophisticated algorithms often led to tiny improvements at the cost of an exponential increase of carbon emissions. Through this paper, we aim to shed light on the problem of carbon footprint and energy consumption of recommender systems, and we make the first step towards the development of sustainability-aware recommendation algorithms.