• Corpus ID: 169373869

First Do No Harm: Considering and Minimizing Harm in Recommender Systems Designed for Engendering Health

@inproceedings{Ekstrand2016FirstDN,
  title={First Do No Harm: Considering and Minimizing Harm in Recommender Systems Designed for Engendering Health},
  author={Jennifer D. Ekstrand and Michael D. Ekstrand},
  year={2016}
}
No Paper Link Available
10 Citations
Background Citations
8

10 Citations

Citation Type

Citation Type

An Overview of Recommendation Techniques and Their Applications in Healthcare
TLDR
A comprehensive review of typical recommendation techniques and their applications in the field of healthcare, namely, content-based, collaborative filtering (CF)-based, and hybrid methods is provided.
Generating Recommendations From Multiple Data Sources: A Methodological Framework for System Design and Its Application
TLDR
This article presents a methodological framework that can drive researchers and developers during the design process of this kind of “holistic” RS, and provides evidence of the framework validity by presenting theDesign process and the evaluation of a food RS based on holistic principles.
Ethics in Neuromarketing and its Implications on Business to Stay Vigilant
Neuromarketing is an emerging field in which academic and industry research employ neuroscience techniques to understand the consumers’ mind by explaining consumers’ preferences, motivations, and…
Privacy Issues in Holistic Recommendations
TLDR
It is emphasized that a holistic recommender should be fair, explainable and privacy-preserving to ensure the ethicality of the recommendation process and propose some preliminary suggestions to face the emergent issues with reference to privacy in the recommendation domain.
The Users' Perspective on the Privacy-Utility Trade-offs in Health Recommender Systems
Healthrecsys: Sistema recomendador para la salud
Cuando se habla de informacion de salud en Internet, inmediatamente se piensa en informacion procedente de colecciones dirigidas por profesionales y por otras entidades que estan en continua…
Designing and Evaluating Student-facing Learning Dashboards: Lessons Learnt
Through the rise of on-line education, an abundance of learner data is generated and gathered. While Educational Data Mining provides insights algorithmically to better understand students, Learning…
Long-term performance of collaborative filtering based recommenders in temporally evolving systems
HealthRecSys: A semantic content-based recommender system to complement health videos
TLDR
This study demonstrates the feasibility of using a semantic content-based recommender system to enrich YouTube health videos by finding the majority of websites recommended by this system for health videos were relevant, based on ratings by health professionals.
Recommender Systems for Health Informatics: State-of-the-Art and Future Perspectives
TLDR
This work provides a three-part research framework to access health recommender systems, suggesting to incorporate domain understanding, evaluation and specific methodology into the development process.

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