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Controlling Spotify Recommendations

, , , and . Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, page 101-109. ACM, (July 2018)
DOI: 10.1145/3209219.3209223

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Controlling Spotify Recommendations, , , and . Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, page 101-109. ACM, (July 2018)Coordinating learning analytics policymaking and implementation at scale., , , , , , , , , and 1 other author(s). Br. J. Educ. Technol., 51 (4): 938-954 (2020)"Knowing me, knowing you": personalized explanations for a music recommender system., , and . User Model. User Adapt. Interact., 32 (1-2): 215-252 (2022)Classifeye: Classification of Personal Characteristics Based on Eye Tracking Data in a Recommender System Interface., , and . IUI Workshops, volume 2903 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)To explain or not to explain: the effects of personal characteristics when explaining music recommendations., , , and . IUI, page 397-407. ACM, (2019)Your Eyes Explain Everything: Exploring the Use of Eye Tracking to Provide Explanations On-the-fly., , and . IntRS@RecSys, volume 2948 of CEUR Workshop Proceedings, page 89-100. CEUR-WS.org, (2021)What\textquotesingles in a User? Towards Personalising Transparency for Music Recommender Interfaces, , , and . Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, page 173-182. ACM, (July 2020)Report on the 1st Workshop on Measuring the Quality of Explanations in Recommender Systems (QUARE 2022) at SIGIR 2022., , , , and . SIGIR Forum, 56 (2): 11:1-11:16 (December 2022)A qualitative evaluation of a learning dashboard to support advisor-student dialogues., , , , and . LAK, page 56-60. ACM, (2018)Card-based approach to coordinate Learning Analytics policymaking and implementation at scale., , , and . EC-TEL (Impact Papers), volume 2676 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)