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Explaining Call Recommendations in Nursing Homes: a User-Centered Design Approach for Interacting with Knowledge-Based Health Decision Support Systems

, , , , and . 27th International Conference on Intelligent User Interfaces, page 162-172. ACM, (March 2022)
DOI: 10.1145/3490099.3511158

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Non-Uniform Information Access in Collaborative Information Retrieval.. SIGIR Forum, 51 (3): 163-164 (2017)Effects of personal characteristics in control-oriented user interfaces for music recommender systems., , , and . User Model. User Adapt. Interact., 30 (2): 199-249 (2020)AHMoSe: A Knowledge-Based Visual Support System for Selecting Regression Machine Learning Models., , , , and . CoRR, (2021)Depicting Recommendations in Academia: How ResearchGate Communicates with Its Users (via Design or upon Request) About Recommender Algorithms., , , , and . DIONE, volume 378 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 3-25. Springer, (2021)What's in a User? Towards Personalising Transparency for Music Recommender Interfaces., , , and . UMAP, page 173-182. ACM, (2020)GaCoVi: a Correlation Visualization to Support Interpretability-Aware Feature Selection for Regression Models., , and . EuroVis (Short Papers), page 127-131. Eurographics Association, (2020)Trespassing the gates of research: identifying algorithmic mechanisms that can cause distortions and biases in academic social media., , , , , and . Online Inf. Rev., 46 (5): 993-1013 (2022)Perception of Fairness in Group Music Recommender Systems., , and . IUI, page 302-306. ACM, (2021)Designing Augmented Reality Applications for Personal Health Decision-Making., , , , and . HICSS, page 1-10. ScholarSpace, (2019)To explain or not to explain: the effects of personal characteristics when explaining music recommendations., , , and . IUI, page 397-407. ACM, (2019)