On this page, we present our recent publications and the resources on multi-method evaluation.
Bauer, Christine (2021). Multi-Method Evaluation for Adaptive Systems. 29th Conference on User Modeling, Adaptation and Personalization (UMAP 2021), Utrecht, The Netherlands, online, 21-25 June, pp 323-325. DOI: 10.1145/3450613.3457122 [paper]
Jannach, Dietmar & Bauer, Christine (2020). Escaping the McNamara Fallacy: Toward More Impactful Recommender Systems Research. AI Magazine, 41(4), pp 79-95. DOI: 10.1609/aimag.v41i4.531274
Bauer, Christine (2020). Multi-Method Evaluation: Leveraging Multiple Methods to Answer What You Were Looking For. Proceedings of the 2020 Conference on Human Information Interaction and Retrieval (CHIIR 2020). Vancouver BC, Canada, 14-18 March, pp 472-474. DOI: 10.1145/3343413.3378015 [paper]
Bauer, Christine & Zangerle, Eva (2019). Leveraging Multi-Method Evaluation for Multi-Stakeholder Settings. Proceedings of the 1st Workshop on the Impact of Recommender Systems (ImpactRS 2019), part of the 13th ACM Conference on Recommender Systems (RecSys 2019), Copenhagen, Denmark, 19 September, CEUR-WS.org, Vol-2462. [paper] [poster]
Celik, Ilknur, Torre, Ilaria, Koceva, Frosina, Bauer, Christine, Zangerle, Eva & Knijnenburg, Bart (2018). UMAP 2018 Intelligent User-Adapted Interfaces: Design and Multi-Modal Evaluation (IUadaptMe) Workshop Chairs’ Welcome & Organization. UMAP ’18 Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization. Singapore, 8 July, ACM, 137-139. DOI: 10.1145/3213586.3226202 [paper]
Christine Bauer’s tutorial on “Multi-method evaluation for adaptive systems” at the 29th Conference on User Modeling, Adaptation and Personalization (UMAP 2021), online, on 25 June 2021. [slides]
Christine Bauer’s interactive teaching session on “Answering the right questions: Leveraging multiple methods to answer what you were looking for” at the ACM Summer School on Recommender Systems 2019 (RecSys Summer School 2019), Gothenburg, Sweden, on 13 September 2019. [slides]