200 citations
- Graz University of TechnologyAT52 papers
- Johannes Kepler University of LinzAT9 papers
- University of GrazAT7 papers
- Technical University of MunichDE4 papers
- Washington University in St. LouisUS4 papers
- GESIS - Leibniz Institute for the Social SciencesDE3 papers
- Pontificia Universidad Católica de ChileCL3 papers
- Tallinn UniversityEE3 papers
- Austrian Academy of SciencesAT2 papers
- Central Institution for Meteorology and GeodynamicsAT2 papers
- Institute of Electrical and Electronics EngineersUS2 papers
- Institut für InformationsverarbeitungDE2 papers
6 papers · 1 filter
A Study of Performance and Interaction Patterns in Hand and Tangible Interaction in Tabletop Mixed Reality
Carlos Mosquera, Neven Elsayed, Ernst Kruijff +2
This paper presents a comprehensive study of virtual 3D object manipulation along 4DoF on real surfaces in mixed reality (MR), using hand-based and tangible interactions. A custom…
Multistakeholder Fairness in Tourism: What can Algorithms learn from Tourism Management?
Peter Muellner, Anna Schreuer, Simone Kopeinik +2
Algorithmic decision-support systems, i.e., recommender systems, are popular digital tools that help tourists decide which places and attractions to explore. However, algorithms of…
A Multistakeholder Approach to Value-Driven Co-Design of Recommender System Evaluation Metrics in Digital Archives
Florian Atzenhofer-Baumgartner, Georg Vogeler, Dominik Kowald
This paper presents the first multistakeholder approach for translating diverse stakeholder values into an evaluation metric setup for Recommender Systems (RecSys) in digital archi…
Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations
Andrea Forster, Simone Kopeinik, Denic Helic +2
Point-of-interest (POI) recommender systems help users discover relevant locations, but their effectiveness is often compromised by popularity bias, which disadvantages less popula…
Impacts of Mainstream-Driven Algorithms on Recommendations for Children Across Domains: A Reproducibility Study
Robin Ungruh, Alejandro Bellogín, Dominik Kowald +1
Children are often exposed to items curated by recommendation algorithms. Yet, research seldom considers children as a user group, and when it does, it is anchored on datasets wher…
Hybrid Personalization Using Declarative and Procedural Memory Modules of the Cognitive Architecture ACT-R
Kevin Innerebner, Dominik Kowald, Markus Schedl +1
Recommender systems often rely on sub-symbolic machine learning approaches that operate as opaque black boxes. These approaches typically fail to account for the cognitive processe…