Green Recommender Systems

A new paper from our group on Green Recommender Systems examines strategies to reduce the energy and carbon footprint of recommendation pipelines while maintaining recommendation quality. The work evaluates efficiency-aware algorithms and measurement practices, and proposes practical guidelines for researchers and practitioners aiming to make recommender systems more sustainable.

Read the full paper:

• ACM Digital Library: https://dl.acm.org/doi/10.1145/3768626
• DOI: https://doi.org/10.1145/3768626

This work builds on and extends collaborations with visiting researchers from the University of Siegen — see our earlier post about their visit: Visiting Researchers from University of Siegen