Abstract
In the rapidly evolving landscape of technology and sustainability, leveraging Recommender Systems has emerged as a powerful tool for driving positive change. With a foundation in AI and data analytics, Recommender Systems can be effective in various domains, from e-commerce to energy management and well-being. By harnessing the power of recommendation algorithms under a holistic perspective, organizations and researchers can guide users towards more sustainable choices and behaviors, contributing to broader environmental and social goals. With this aim, our workshop provides a unique opportunity for researchers, practitioners, and stakeholders to explore the integration of sustainability principles into Recommender Systems. Through presentations, discussions, and panels, participants explore the theoretical foundations, practical implementations, and ethical and environmental issues of sustainable Recommender Systems. By fostering collaboration and knowledge exchange, the workshop aims to catalyze innovation and inspire collective action towards a more sustainable future.
| Original language | English |
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| Title of host publication | RecSys 2024 - Proceedings of the 18th ACM Conference on Recommender Systems |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 1239-1241 |
| Number of pages | 3 |
| ISBN (Electronic) | 9798400705052 |
| DOIs | |
| Publication status | Published - 8 Oct 2024 |
| Event | 18th ACM Conference on Recommender Systems, RecSys 2024 - Bari, Italy Duration: 14 Oct 2024 → 18 Oct 2024 https://recsys.acm.org/recsys24/ |
Publication series
| Name | RecSys 2024 - Proceedings of the 18th ACM Conference on Recommender Systems |
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Conference
| Conference | 18th ACM Conference on Recommender Systems, RecSys 2024 |
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| Abbreviated title | RecSys '24 |
| Country/Territory | Italy |
| City | Bari |
| Period | 14/10/24 → 18/10/24 |
| Internet address |
Keywords
- Behavioural Change
- Recommendation
- Social Good
- Sustainability
- Sustainable Development Goals
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems
- Software
- Control and Systems Engineering