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GreenDB: Toward a Product-by-Product Sustainability Database. (arXiv:2205.02908v1 [cs.LG])
Web: http://arxiv.org/abs/2205.02908
May 9, 2022, 1:11 a.m. | Sebastian Jäger, Jessica Greene, Max Jakob, Ruben Korenke, Tilman Santarius, Felix Biessmann
cs.LG updates on arXiv.org arxiv.org
The production, shipping, usage, and disposal of consumer goods have a
substantial impact on greenhouse gas emissions and the depletion of resources.
Modern retail platforms rely heavily on Machine Learning (ML) for their search
and recommender systems. Thus, ML can potentially support efforts towards more
sustainable consumption patterns, for example, by accounting for sustainability
aspects in product search or recommendations. However, leveraging ML potential
for reaching sustainability goals requires data on sustainability.
Unfortunately, no open and publicly available database integrates …
More from arxiv.org / cs.LG updates on arXiv.org
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