Recommender systems for sustainability: overview and research issues

Front Big Data. 2023 Oct 30:6:1284511. doi: 10.3389/fdata.2023.1284511. eCollection 2023.

Abstract

Sustainability development goals (SDGs) are regarded as a universal call to action with the overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity for all people. In order to achieve these objectives, different AI technologies play a major role. Specifically, recommender systems can provide support for organizations and individuals to achieve the defined goals. Recommender systems integrate AI technologies such as machine learning, explainable AI (XAI), case-based reasoning, and constraint solving in order to find and explain user-relevant alternatives from a potentially large set of options. In this article, we summarize the state of the art in applying recommender systems to support the achievement of sustainability development goals. In this context, we discuss open issues for future research.

Keywords: artificial intelligence; machine learning; recommender systems; sustainability; sustainability development goals.

Publication types

  • Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The presented work has been developed within the TU Graz internal project AI4Sustainability. This work was supported by TU Graz Open Access Publishing Fund.