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Auflistung nach Schlagwort "User Study"

1 - 5 von 5
  • Konferenzbeitrag
    Design of a Knowledge-Based Recommender System for Recipes from an End-User Perspective
    (Mensch und Computer 2021 - Tagungsband, 2021) Niessner, Julia; Ludwig, Thomas
    Nowadays, recommender systems are a fundamental part of several online services. However, most of these systems rely on collective user data and ratings or a preselection of parameters to derive appropriate recommendations. Within this paper, we examine recommendations without previous user data. We therefore designed and evaluated a knowledge-based recommender system by turning to recipe recommendations that offer alternatives for favorite recipes. We introduce and compare three versions of a given algorithm. Our evaluation shows that the knowledge-based approach may serve as a good start for deriving appropriate recommendations without prior user data. Moreover, we show that end-users’ assumptions about decisive criteria of a recommender system do not necessarily match the later actual decisive criteria.
  • Konferenzbeitrag
    Explanation Needs in Automated Driving: Insights from German Driving Education and Vehicle Acquisition
    (Proceedings of Mensch und Computer 2024, 2024) Manger, Carina; Albrecht, Kathrin; Riener, Andreas
    As driving assistance driving systems become increasingly advanced, a correct understanding of the functionality of these systems is crucial for safe use. In this work we explored drivers’ explanation needs and current explanation methods from an important but underlooked perspective: driver training and vehicle acquisition. In a two-step approach, we conducted expert interviews with n = 7 driving instructors and vehicle salespeople in Germany and validated these results with an online survey of n = 105. Our results show that Driver Assistance Systems (DASs) and Advanced Driver Assistance Systems (ADASs), are currently covered in both driver training and vehicle acquisition but to a varying extent and in a very application-oriented manner. A drivers’ tendency for preferring comparative explanations that build upon knowledge about similar systems was found. Based on the combined results, we emphasize the need for mandatory and standardized explanation methods to ensure a safe transition to automated driving.
  • Konferenzbeitrag
    Item Familiarity as a Possible Confounding Factor in User-Centric Recommender Systems Evaluation
    (i-com: Vol. 14, No. 1, 2015) Jannach, Dietmar; Lerche, Lukas; Jugovac, Michael
    User studies play an important role in academic research in the field of recommender systems as they allow us to assess quality factors other than the predictive accuracy of the underlying algorithms. User satisfaction is one such factor that is often evaluated in laboratory settings and in many experimental designs one task of the participants is to assess the suitability of the system-generated recommendations. The effort required by the user to make such an assessment can, however, depend on the user’s familiarity with the presented items and directly impact on the reported user satisfaction. In this paper, we report the results of a preliminary recommender systems user study using Mechanical Turk, which indicates that item familiarity is strongly correlated with overall satisfaction.
  • Konferenzbeitrag
    Non-Contact In-Car Monitoring of Heart Rate: Evaluating the Eulerian Video Magnification Algorithm in a Driving Simulator Study
    (Proceedings of Mensch und Computer 2024, 2024) Renner, Philipp; Gleichauf, Johanna; Winkelmann, Sven
    Monitoring drivers’ health is crucial for saving lives in emergencies and enabling in-car health applications. The state of the art in pulse monitoring is contact-based sensors which impair the driving experience and have to be applied manually before driving. This paper focuses on automated hyper parameter optimizing the Eulerian Video Magnification (EVM) algorithm, which detects heart rates through non-contact facial camera images, for use in driving scenarios. We conducted a user study where 21 participants performed a driving simulation while their heart rates were recorded by a wearable fitness tracker (serving as ground truth) and facial images with an RGB camera. Our findings indicate that, despite using the optuna library for hyper parameter tuning, the Eulerian Video Magnification algorithm is insufficient for accurate pulse detection in a driving simulator environment.
  • Konferenzbeitrag
    Perceptions of a Help-Requesting Robot - Effects of Eye-Expressions, Colored Lights and Politeness of Speech
    (Mensch und Computer 2019 - Tagungsband, 2019) Westhoven, Martin; van der Grinten, Tim; Mueller, Steffen
    In this paper we report results from a web- and video-based study on the perception of a request for help from a robot head. Colored lights, eye-expressions and politeness of speech were varied. We measured effects on expression identification, hedonic user experience, perceived politeness, and help intention. Additionally, sociodemographic data, a 'face blindness' questionnaire, and negative attitudes towards robots were collected to control for possible influences on the dependent variables. A total of n=139 participants were included in the analysis. Significant differences were found for the identification performance for our intended eye-expressions, for perceived politeness, help intentions and hedonic user experience. Especially for the negative attitudes towards robots, we found significant relationships with perceived politeness and help intentions.