Computational Methods for Designing Human-Centered Recommender Systems: A Case Study Approach Intersecting Visual Arts and Healthcare
Recommender Systems (RecSys) are essential tools in sectors like e-commerce, entertainment, and social media, providing personalized user experiences. Their impact is also growing in education, healthcare, tourism, transport, and logistics, enhancing decision-making and user engagement. Hence, designing modern RecSys requires a multi-disciplinary approach, incorporating machine learning, information retrieval, and human-computer interaction (HCI). This tutorial focuses on human-centric RecSys design, emphasizing both computational methods and user-centered principles. Participants will learn fundamental concepts, advanced algorithms, and practical implementation, with case studies linking visual arts and healthcare applications.
Authors
- Bereket Abera Yilma (ORCID: https://orcid.org/0000-0001-7210-9919)
Institutions
- University of Luxembourg (LU)
Publication Details
- Published
- 2024-10-08
- DOI
- https://doi.org/10.1145/3640457.3687091
- Primary Topic
- Image Retrieval and Classification Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00